List of the Top 23 Database Software for Amazon S3 in 2025

StarTree Cloud functions as a fully-managed platform for real-time analytics, optimized for online analytical processing (OLAP) with exceptional speed and scalability tailored for user-facing applications. Leveraging the capabilities of Apache Pinot, it offers enterprise-level reliability along with advanced features such as tiered storage, scalable upserts, and a variety of additional indexes and connectors. The platform seamlessly integrates with transactional databases and event streaming technologies, enabling the ingestion of millions of events per second while indexing them for rapid query performance. Available on popular public clouds or for private SaaS deployment, StarTree Cloud caters to diverse organizational needs. Included within StarTree Cloud is the StarTree Data Manager, which facilitates the ingestion of data from both real-time sources—such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda—and batch data sources like Snowflake, Delta Lake, Google BigQuery, or object storage solutions like Amazon S3, Apache Flink, Apache Hadoop, and Apache Spark. Moreover, the system is enhanced by StarTree ThirdEye, an anomaly detection feature that monitors vital business metrics, sends alerts, and supports real-time root-cause analysis, ensuring that organizations can respond swiftly to any emerging issues. This comprehensive suite of tools not only streamlines data management but also empowers organizations to maintain optimal performance and make informed decisions based on their analytics.

The landscape of access and access management has evolved into a more intricate and often frustrating challenge. strongDM reimagines access by focusing on the individuals who require it, resulting in a solution that is not only user-friendly but also maintains rigorous security and compliance standards. This innovative approach is referred to as People-First Access. Users benefit from quick, straightforward, and traceable access to essential resources, while administrators enjoy enhanced control that reduces the risk of unauthorized and excessive permissions. Additionally, teams in IT, Security, DevOps, and Compliance can effortlessly track activities with detailed audit logs answering critical questions about actions taken, locations, and timings. The system integrates seamlessly and securely across various environments and protocols, complemented by reliable 24/7 customer support to ensure optimal functionality. This comprehensive approach guarantees both efficiency and security in managing access.

Amazon Athena is an interactive query service that makes it easy to analyze data stored in Amazon S3 by utilizing standard SQL. Being a serverless offering, it removes the burden of infrastructure management, enabling users to pay only for the queries they run. Its intuitive interface allows you to directly point to your data in Amazon S3, define the schema, and start querying using standard SQL commands, with most results generated in just a few seconds. Athena bypasses the need for complex ETL processes, empowering anyone with SQL knowledge to quickly explore extensive datasets. Furthermore, it provides seamless integration with AWS Glue Data Catalog, which helps in creating a unified metadata repository across various services. This integration not only allows users to crawl data sources for schema identification and update the Catalog with new or modified table definitions, but also aids in managing schema versioning. Consequently, this functionality not only simplifies data management but also significantly boosts the efficiency of data analysis within the AWS ecosystem. Overall, Athena's capabilities make it an invaluable tool for data analysts looking for rapid insights without the overhead of traditional data preparation methods.

Scaleway provides a cloud solution that genuinely meets your needs. With a solid framework designed to foster digital advancement, it encompasses a high-performance cloud ecosystem alongside extensive eco-friendly data centers. Our platform is customized for developers and growing businesses, offering all the tools required for seamless creation, deployment, and scaling of your infrastructure. We deliver a diverse array of services, which includes Compute, GPU, Bare Metal, and Containers, in addition to Evolutive & Managed Storage options. Furthermore, our capabilities extend into Networking and IoT, showcasing a broad variety of dedicated servers suitable for even the most demanding tasks. Alongside our premium dedicated servers, we also provide Web Hosting and Domain Name Services. You can take advantage of our specialized knowledge to securely manage your hardware in our resilient, high-performance data centers, with flexible options for Private Suites & Cages, and various Rack configurations. Scaleway's six cutting-edge data centers across Europe enable us to offer cloud solutions to clients in more than 160 countries worldwide. Our dedicated Excellence team is on hand 24/7 throughout the year, ensuring we are always prepared to assist our customers in leveraging, refining, and maximizing their platforms with the support of skilled professionals, fostering an ongoing culture of improvement and innovation. This commitment to customer service and technological advancement sets Scaleway apart in the cloud industry.

Amazon Aurora is a cloud-native relational database designed to work seamlessly with both MySQL and PostgreSQL, offering the high performance and reliability typically associated with traditional enterprise databases while also providing the cost-effectiveness and simplicity of open-source solutions. Its performance is notably superior, achieving speeds up to five times faster than standard MySQL databases and three times faster than standard PostgreSQL databases. Moreover, it combines the security, availability, and reliability expected from commercial databases, all at a remarkably lower price point—specifically, only one-tenth of the cost. Managed entirely by the Amazon Relational Database Service (RDS), Aurora streamlines operations by automating critical tasks such as hardware provisioning, database configuration, patch management, and backup processes. This database features a fault-tolerant storage architecture that can automatically scale to support database instances as large as 64TB. Additionally, Amazon Aurora enhances performance and availability through capabilities like up to 15 low-latency read replicas, point-in-time recovery, continuous backups to Amazon S3, and data replication across three separate Availability Zones, all of which improve data resilience and accessibility. These comprehensive features not only make Amazon Aurora an attractive option for businesses aiming to harness the cloud for their database requirements but also ensure they can do so while enjoying exceptional performance and security measures. Ultimately, adopting Amazon Aurora can lead to reduced operational overhead and greater focus on innovation.

Retool is a versatile platform that empowers developers to merge the advantages of conventional software development with an intuitive drag-and-drop interface and AI capabilities, allowing for the rapid creation of internal tools. Each tool is deployable in various environments, can be debugged using your existing toolchain, and is easily shareable at any scale, guaranteeing high-quality software as a standard. Major companies like Amazon, American Express, and OpenAI rely on Retool for essential custom software solutions in areas such as operations, billing, and customer support, highlighting its effectiveness in meeting critical business needs. This adaptability makes Retool an invaluable asset for teams looking to streamline their development processes.

NAKIVO Backup & Replication delivers a highly regarded, efficient, and cost-effective solution for backup, ransomware recovery, and disaster recovery, applicable across virtual, physical, and cloud settings. This solution excels in performance, dependability, and management, catering to the needs of small and medium-sized businesses, large enterprises, and managed service providers alike. Its versatility ensures that various types of organizations can effectively safeguard their data and maintain operational continuity.

StarfishETL functions as a Cloud iPaaS solution, enabling the seamless integration of virtually any application with another, provided that both have an accessible API. This capability empowers StarfishETL users to exercise full control over their data initiatives, allowing them to establish distinctive and scalable data connections tailored to their specific needs. By facilitating such flexibility, StarfishETL enhances the overall efficiency of data management and integration processes for its clients.

Establish your own data marketplace to generate additional income from your existing data assets. The narrative emphasizes essential principles that simplify, secure, and enhance the process of buying or selling data. It's crucial to verify that the data at your disposal aligns with your quality standards. Understanding the origins and collection methods of the data is vital for maintaining integrity. By easily accessing new supply and demand, you can develop a more nimble and inclusive data strategy. You gain comprehensive control over your data strategy through complete end-to-end visibility of all inputs and outputs. Our platform streamlines the most labor-intensive and time-consuming elements of data acquisition, enabling you to tap into new data sources in a matter of days rather than months. With features like filters, budget management, and automatic deduplication, you will only pay for what you truly need, ensuring maximum efficiency in your data operations. This approach not only saves time but also enhances the overall effectiveness of your data-driven initiatives.

Trino is an exceptionally swift query engine engineered for remarkable performance. This high-efficiency, distributed SQL query engine is specifically designed for big data analytics, allowing users to explore their extensive data landscapes. Built for peak efficiency, Trino shines in low-latency analytics and is widely adopted by some of the biggest companies worldwide to execute queries on exabyte-scale data lakes and massive data warehouses. It supports various use cases, such as interactive ad-hoc analytics, long-running batch queries that can extend for hours, and high-throughput applications that demand quick sub-second query responses. Complying with ANSI SQL standards, Trino is compatible with well-known business intelligence tools like R, Tableau, Power BI, and Superset. Additionally, it enables users to query data directly from diverse sources, including Hadoop, S3, Cassandra, and MySQL, thereby removing the burdensome, slow, and error-prone processes related to data copying. This feature allows users to efficiently access and analyze data from different systems within a single query. Consequently, Trino's flexibility and power position it as an invaluable tool in the current data-driven era, driving innovation and efficiency across industries.

SQL Safe Backup empowers database administrators to swiftly perform backups and restorations across Microsoft SQL Servers. Distinct from its rivals, it offers virtual databases that enable immediate recovery, along with centralized management capabilities for multiple SQL Servers, and it also provides alert notifications to inform users of the success or failure of various operations. This comprehensive approach ensures that database administrators can maintain data integrity and availability with minimal downtime.

Materialize is a cutting-edge reactive database that facilitates the incremental updating of views, making it easier for developers to engage with streaming data using familiar SQL syntax. This platform stands out due to its capability to directly interface with various external data sources without necessitating extensive pre-processing steps. Users can connect to live streaming sources like Kafka and Postgres databases, as well as utilize change data capture (CDC) mechanisms, while also having the option to access historical data from files or S3 storage. Materialize allows for the execution of queries, the performance of joins, and the transformation of diverse data sources through standard SQL, resulting in dynamically updated Materialized views. As new data flows in, queries remain active and are consistently refreshed, empowering developers to easily create real-time applications or data visualizations. Additionally, the process of building applications that leverage streaming data is simplified, often requiring minimal SQL code, which greatly boosts development efficiency. Ultimately, with Materialize, developers can dedicate their efforts to crafting innovative solutions instead of getting overwhelmed by intricate data management challenges, thus unlocking new possibilities in data-driven projects.

A robust vector database tailored for efficient similarity searches at scale, Milvus is both open-source and exceptionally fast. It enables the storage, indexing, and management of extensive embedding vectors generated by deep neural networks or other machine learning methodologies. With Milvus, users can establish large-scale similarity search services in less than a minute, thanks to its user-friendly and intuitive SDKs available for multiple programming languages. The database is optimized for performance on various hardware and incorporates advanced indexing algorithms that can accelerate retrieval speeds by up to 10 times. Over a thousand enterprises leverage Milvus across diverse applications, showcasing its versatility. Its architecture ensures high resilience and reliability by isolating individual components, which enhances operational stability. Furthermore, Milvus's distributed and high-throughput capabilities position it as an excellent option for managing large volumes of vector data. The cloud-native approach of Milvus effectively separates compute and storage, facilitating seamless scalability and resource utilization. This makes Milvus not just a database, but a comprehensive solution for organizations looking to optimize their data-driven processes.

Tabular is a cutting-edge open table storage solution developed by the same team that created Apache Iceberg, facilitating smooth integration with a variety of computing engines and frameworks. By utilizing this advanced technology, users can dramatically decrease both query durations and storage costs, potentially achieving reductions of up to 50%. The platform centralizes the application of role-based access control (RBAC) policies, thereby ensuring the consistent maintenance of data security. It supports multiple query engines and frameworks, including Athena, BigQuery, Redshift, Snowflake, Databricks, Trino, Spark, and Python, which allows for remarkable flexibility. With features such as intelligent compaction, clustering, and other automated data services, Tabular further boosts efficiency by lowering storage expenses and accelerating query performance. It facilitates unified access to data across different levels, whether at the database or table scale. Additionally, the management of RBAC controls is user-friendly, ensuring that security measures are both consistent and easily auditable. Tabular stands out for its usability, providing strong ingestion capabilities and performance, all while ensuring effective management of RBAC. Ultimately, it empowers users to choose from a range of high-performance compute engines, each optimized for their unique strengths, while also allowing for detailed privilege assignments at the database, table, or even column level. This rich combination of features establishes Tabular as a formidable asset for contemporary data management, positioning it to meet the evolving needs of businesses in an increasingly data-driven landscape.

Hue offers an outstanding querying experience thanks to its state-of-the-art autocomplete capabilities and advanced components in the query editor. Users can effortlessly traverse tables and storage browsers, applying their familiarity with data catalogs to find the necessary information. This feature not only helps in pinpointing data within vast databases but also encourages self-documentation. Moreover, the platform aids users in formulating SQL queries while providing rich previews for links, facilitating direct sharing within Slack right from the editor. There is an array of applications designed specifically for different querying requirements, and data sources can be easily navigated using the user-friendly browsers. The editor is particularly proficient in handling SQL queries, enhanced with smart autocomplete, risk notifications, and self-service troubleshooting options. Dashboards are crafted to visualize indexed data effectively, yet they also have the capability to execute queries on SQL databases. Users can now search for particular cell values in tables, with results conveniently highlighted for quick identification. Additionally, Hue's SQL editing features rank among the best in the world, guaranteeing a seamless and productive experience for all users. This rich amalgamation of functionalities positions Hue as a formidable tool for both data exploration and management, making it an essential resource for any data professional.

Streamline your operations and cut costs by utilizing straightforward open-source solutions to simplify your data pipelines. From the initial stages of data ingestion to final visualization, every element is cohesively integrated, managed entirely, and highly dependable, ensuring that your engineering team finds joy in handling data. You have the choice of using any of DoubleCloud’s managed open-source services or leveraging the full range of the platform’s features, which encompass data storage, orchestration, ELT, and real-time visualization capabilities. We provide top-tier open-source services including ClickHouse, Kafka, and Airflow, which can be deployed on platforms such as Amazon Web Services or Google Cloud. Additionally, our no-code ELT tool facilitates immediate data synchronization across different systems, offering a rapid, serverless solution that meshes seamlessly with your current infrastructure. With our managed open-source data visualization tools, generating real-time visual interpretations of your data through interactive charts and dashboards is a breeze. Our platform is specifically designed to optimize the daily workflows of engineers, making their tasks not only more efficient but also more enjoyable. Ultimately, this emphasis on user-friendliness and convenience is what distinguishes us from competitors in the market. We believe that a better experience leads to greater productivity and innovation within teams.

LanceDB is a user-friendly, open-source database tailored specifically for artificial intelligence development. It boasts features like hyperscalable vector search and advanced retrieval capabilities designed for Retrieval-Augmented Generation (RAG), as well as the ability to handle streaming training data and perform interactive analyses on large AI datasets, positioning it as a robust foundation for AI applications. The installation process is remarkably quick, allowing for seamless integration with existing data and AI workflows. Functioning as an embedded database—similar to SQLite or DuckDB—LanceDB facilitates native object storage integration, enabling deployment in diverse environments and efficient scaling down when not in use. Whether used for rapid prototyping or extensive production needs, LanceDB delivers outstanding speed for search, analytics, and training with multimodal AI data. Moreover, several leading AI companies have efficiently indexed a vast array of vectors and large quantities of text, images, and videos at a cost significantly lower than that of other vector databases. In addition to basic embedding capabilities, LanceDB offers advanced features for filtering, selection, and streaming training data directly from object storage, maximizing GPU performance for superior results. This adaptability not only enhances its utility but also positions LanceDB as a formidable asset in the fast-changing domain of artificial intelligence, catering to the needs of various developers and researchers alike.

Turso is a distributed database solution that aligns with SQLite, crafted to provide low-latency data accessibility across diverse environments, including online, offline, and on-device settings. Built on the principles of libSQL, an open-source derivative of SQLite, Turso empowers developers to strategically position databases closer to their users, substantially enhancing application performance. Its seamless integration with a variety of frameworks, languages, and infrastructure providers facilitates streamlined data management for applications leveraging large language models and AI agents. Notable features of Turso encompass unlimited databases, the capability for instant change rollbacks through branching, and robust native vector search functionalities at scale, which allow for efficient parallel searches across multiple users, instances, or contexts via SQL database integration. Security is a key focus for the platform, which incorporates encryption for stored and transmitted data while adopting an API-first strategy that simplifies the management of databases programmatically. Furthermore, Turso's flexible architecture is designed for rapid scaling, allowing it to adapt to the evolving needs of applications, thus making it an ideal choice for developers navigating today's dynamic data-centric environment. As a result, Turso stands out as a powerful tool for developers who prioritize performance, security, and scalability in their database solutions.

Apache DataFusion is a highly adaptable and capable query engine developed in Rust, which utilizes Apache Arrow for efficient in-memory data handling. It is intended for developers who are working on data-centric systems, including databases, data frames, machine learning applications, and real-time data streaming solutions. Featuring both SQL and DataFrame APIs, DataFusion offers a vectorized, multi-threaded execution engine that efficiently manages data streams while accommodating a variety of partitioned data sources. It supports numerous native file formats, including CSV, Parquet, JSON, and Avro, and integrates seamlessly with popular object storage services such as AWS S3, Azure Blob Storage, and Google Cloud Storage. The architecture is equipped with a sophisticated query planner and an advanced optimizer, which includes features like expression coercion, simplification, and distribution-aware optimizations, as well as automatic join reordering for enhanced performance. Additionally, DataFusion provides significant customization options, allowing developers to implement user-defined scalar, aggregate, and window functions, as well as integrate custom data sources and query languages, thereby enhancing its utility for a wide range of data processing scenarios. This flexibility ensures that developers can effectively adjust the engine to meet their specific requirements and optimize their data workflows.

Amazon QLDB is a fully managed ledger database that provides a transparent, immutable, and cryptographically secure transaction log overseen by a central trusted authority. This service facilitates precise tracking of all data modifications within applications, ensuring a thorough and verifiable historical record of changes over time. Companies frequently use ledgers to document financial and economic transactions, creating a detailed account of their operational activities. Many organizations choose to develop applications that incorporate ledger-like functionalities to maintain an accurate history of their data, which may include tracking financial transactions, verifying data lineage for insurance purposes, or monitoring the flow of goods in a supply chain. By leveraging Amazon QLDB, businesses can circumvent the complex and resource-demanding task of building their own ledger systems, thus enhancing their operational efficiency and productivity. This innovation marks a notable progression for enterprises in search of dependable data management solutions, paving the way for greater transparency and accountability in record-keeping practices. Embracing such advanced technologies can significantly empower organizations to make informed decisions based on reliable data.

TIMi empowers businesses to leverage their corporate data for innovative ideas and expedited decision-making like never before. At its core lies TIMi's Integrated Platform, featuring a cutting-edge real-time AUTO-ML engine along with advanced 3D VR segmentation and visualization capabilities. With unlimited self-service business intelligence, TIMi stands out as the quickest option for executing the two most essential analytical processes: data cleansing and feature engineering, alongside KPI creation and predictive modeling. This platform prioritizes ethical considerations, ensuring no vendor lock-in while upholding a standard of excellence. We promise a working experience free from unforeseen expenses, allowing for complete peace of mind. TIMi’s distinct software framework fosters unparalleled flexibility during exploration and steadfast reliability in production. Moreover, TIMi encourages your analysts to explore even the wildest ideas, promoting a culture of creativity and innovation throughout your organization.

ParadeDB enhances the functionality of Postgres tables by incorporating a column-oriented storage system along with advanced vectorized query execution capabilities. When creating a table, users have the flexibility to choose between row-oriented and column-oriented storage formats. The data for column-oriented tables is efficiently stored in Parquet files and is managed using Delta Lake technology. It boasts a keyword search functionality that utilizes BM25 scoring, customizable tokenizers, and offers support for multiple languages. In addition, ParadeDB facilitates semantic searches that leverage both sparse and dense vectors, allowing users to achieve greater accuracy in results by integrating full-text search with similarity search techniques. Moreover, it maintains adherence to ACID principles, which ensures strong concurrency controls for all transactional operations. ParadeDB also provides seamless compatibility with the wider Postgres ecosystem, encompassing various clients, extensions, and libraries, thus presenting a flexible solution for developers. Ultimately, ParadeDB stands out as a robust option for those in need of enhanced data management and retrieval capabilities within the Postgres framework, making it an excellent choice for performance-driven applications.

SDF stands out as a powerful platform designed for developers who prioritize data, enhancing SQL comprehension across diverse organizations while empowering data teams to fully leverage their data's potential. It incorporates a groundbreaking layer that streamlines the writing and management of queries, supplemented by an analytical database engine that facilitates local execution and an accelerator for optimizing transformation processes. Furthermore, SDF is equipped with proactive quality and governance features, including detailed reports, contracts, and impact analysis tools, all aimed at preserving data integrity and ensuring adherence to regulatory standards. By encapsulating business logic within code, SDF supports the classification and management of various data types, which significantly enhances the clarity and sustainability of data models. Additionally, it seamlessly integrates into existing data workflows, supporting multiple SQL dialects and cloud environments, and is designed to grow in tandem with the increasing demands of data teams. Its open-core architecture, founded on Apache DataFusion, not only allows for customization and extensibility but also fosters a collaborative atmosphere for data development, making it an essential asset for organizations seeking to refine their data strategies. Ultimately, SDF is instrumental in driving innovation and operational efficiency within the realm of data management, serving as a catalyst for improved decision-making and business outcomes.