List of the Top 3 OLAP Databases for TablePlus in 2025

Amazon Redshift stands out as the favored option for cloud data warehousing among a wide spectrum of clients, outpacing its rivals. It caters to analytical needs for a variety of enterprises, ranging from established Fortune 500 companies to burgeoning startups, helping them grow into multi-billion dollar entities, as exemplified by Lyft. The platform is particularly adept at facilitating the extraction of meaningful insights from vast datasets. Users can effortlessly perform queries on large amounts of both structured and semi-structured data throughout their data warehouses, operational databases, and data lakes, utilizing standard SQL for their queries. Moreover, Redshift enables the convenient storage of query results back to an S3 data lake in open formats like Apache Parquet, allowing for further exploration with other analysis tools such as Amazon EMR, Amazon Athena, and Amazon SageMaker. Acknowledged as the fastest cloud data warehouse in the world, Redshift consistently improves its speed and performance annually. For high-demand workloads, the newest RA3 instances can provide performance levels that are up to three times superior to any other cloud data warehouse on the market today. This impressive capability establishes Redshift as an essential tool for organizations looking to optimize their data processing and analytical strategies, driving them toward greater operational efficiency and insight generation. As more businesses recognize these advantages, Redshift’s user base continues to expand rapidly.

Tailored for the enhancement of compute, memory, and storage capabilities, Oxla functions as a self-hosted data warehouse that specializes in managing extensive, low-latency analytics while effectively supporting time-series data. Although cloud data warehouses may be beneficial for many businesses, they do not fit every scenario; as companies grow, the continuous expenses associated with cloud computing can outpace initial savings on infrastructure, particularly in industries that require stringent data governance beyond just VPC and BYOC solutions. Oxla distinguishes itself from both conventional and cloud-based warehouses by optimizing efficiency, enabling the scalability of growing datasets while maintaining predictable costs, whether deployed on-premises or across diverse cloud platforms. The deployment, operation, and upkeep of Oxla can be conveniently handled through Docker and YAML, allowing a variety of workloads to flourish within a single, self-hosted data warehouse. Consequently, Oxla emerges as a customized solution for organizations aiming for both enhanced efficiency and rigorous control in their data management practices, ultimately driving better decision-making and operational performance.

OpenText Analytics Database, formerly known as Vertica Data Platform, is a powerful analytics database designed to provide ultra-fast, scalable analysis of massive data volumes with minimal compute and storage requirements. It enables organizations to unlock real-time insights and operational efficiencies by combining high-speed analytics with integrated machine learning capabilities. The platform’s massively parallel processing (MPP) architecture ensures that complex, resource-intensive queries run efficiently regardless of dataset size. Its columnar storage format optimizes both query speed and storage utilization, significantly reducing disk I/O. OpenText Analytics Database seamlessly integrates with data lakehouse environments, supporting popular formats like Parquet, ORC, AVRO, and native ROS, providing versatile data accessibility. Users can query and analyze data using multiple languages, including SQL, R, Python, Java, and C/C++, catering to a wide range of skill sets from data scientists to business analysts. Built-in machine learning functions enable users to build, test, and deploy predictive models directly within the database, eliminating the need for data movement and accelerating time to insight. Additional in-database analytics functions cover time series analysis, geospatial queries, and event-pattern matching, providing rich data exploration capabilities. Flexible deployment options allow organizations to run the platform on-premises, in the cloud, or in hybrid setups to optimize infrastructure alignment and cost. Supported by OpenText’s professional services, training, and premium support, the Analytics Database empowers businesses to drive revenue growth, enhance customer experiences, and reduce time to market through data-driven strategies.