Ratings and Reviews 0 Ratings
Ratings and Reviews 0 Ratings
Alternatives to Consider
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DragonflyDragonfly acts as a highly efficient alternative to Redis, significantly improving performance while also lowering costs. It is designed to leverage the strengths of modern cloud infrastructure, addressing the data needs of contemporary applications and freeing developers from the limitations of traditional in-memory data solutions. Older software is unable to take full advantage of the advancements offered by new cloud technologies. By optimizing for cloud settings, Dragonfly delivers an astonishing 25 times the throughput and cuts snapshotting latency by 12 times when compared to legacy in-memory data systems like Redis, facilitating the quick responses that users expect. Redis's conventional single-threaded framework incurs high costs during workload scaling. In contrast, Dragonfly demonstrates superior efficiency in both processing and memory utilization, potentially slashing infrastructure costs by as much as 80%. It initially scales vertically and only shifts to clustering when faced with extreme scaling challenges, which streamlines the operational process and boosts system reliability. As a result, developers can prioritize creative solutions over handling infrastructure issues, ultimately leading to more innovative applications. This transition not only enhances productivity but also allows teams to explore new features and improvements without the typical constraints of server management.
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Google Compute EngineGoogle's Compute Engine, which falls under the category of infrastructure as a service (IaaS), enables businesses to create and manage virtual machines in the cloud. This platform facilitates cloud transformation by offering computing infrastructure in both standard sizes and custom machine configurations. General-purpose machines, like the E2, N1, N2, and N2D, strike a balance between cost and performance, making them suitable for a variety of applications. For workloads that demand high processing power, compute-optimized machines (C2) deliver superior performance with advanced virtual CPUs. Memory-optimized systems (M2) are tailored for applications requiring extensive memory, making them perfect for in-memory database solutions. Additionally, accelerator-optimized machines (A2), which utilize A100 GPUs, cater to applications that have high computational demands. Users can integrate Compute Engine with other Google Cloud Services, including AI and machine learning or data analytics tools, to enhance their capabilities. To maintain sufficient application capacity during scaling, reservations are available, providing users with peace of mind. Furthermore, financial savings can be achieved through sustained-use discounts, and even greater savings can be realized with committed-use discounts, making it an attractive option for organizations looking to optimize their cloud spending. Overall, Compute Engine is designed not only to meet current needs but also to adapt and grow with future demands.
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RaimaDBRaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
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NMISFirstWave’s NMIS acts as a robust network management system, encompassing fault detection, performance monitoring, configuration oversight, performance visualizations, and alerts based on specific thresholds. It employs business rules that facilitate tailored notification policies, compatible with various notification methods. Additionally, FirstWave empowers its partners, which include some of the largest telecommunications companies and managed service providers worldwide, to safeguard their clientele against cyber threats, all while swiftly expanding their cybersecurity service revenues on a significant scale. Overall, FirstWave delivers a thorough and integrated solution for network discovery, management, and cybersecurity, catering to its global partners. This holistic approach ensures that partners can effectively combat evolving cyber threats while managing their networks efficiently.
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LogicalDOCLogicalDOC enables organizations worldwide to effectively manage their documents and streamline their workflows. This top-tier document management system (DMS) prioritizes business process automation and efficient content retrieval, empowering teams to create, collaborate, and oversee substantial amounts of documentation seamlessly. Additionally, it consolidates critical company information into a single centralized repository for easy access. Among its standout features are drag-and-drop uploads, forms management, optical character recognition (OCR), duplicate detection, barcode recognition, event logging, document archiving, and integrated workflows that enhance productivity. Experience the benefits firsthand by scheduling a complimentary, no-obligation one-on-one demo today, and discover how LogicalDOC can transform your document management practices.
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MEXCFounded by skilled quantitative trading professionals from major financial hubs including Wall Street, Europe, and Japan, MEXC (formerly MXC) operates as a decentralized entity focused on providing secure, efficient, and user-friendly cryptocurrency trading services for digital asset enthusiasts worldwide. The MEXC platform encompasses five unique business models: Spot Trading, C2C, Derivatives, PoS Pool, and MXC Labs. Utilizing a high-performance mega-transaction matching engine and a distributed "Super Node" initiative, it fosters strong community governance. In addition, the protection of assets is entrusted to leading security firms such as Palmim and Knownsec. MEXC distinguishes itself as a platform deeply rooted in cryptocurrency and backed by experienced blockchain industry experts from renowned financial centers. By emphasizing safety and user satisfaction, MEXC strives to offer smarter and more accessible exchange solutions while aiming to establish itself as a premier cryptocurrency exchange globally. The organization also actively pursues innovation and remains responsive to the dynamic requirements of the cryptocurrency landscape, ensuring it stays ahead in a competitive market.
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ManageEngine EventLog AnalyzerManage Engine's EventLog Analyzer stands out as the most cost-effective security information and event management (SIEM) software in the market. This secure, cloud-based platform encompasses vital SIEM functionalities such as log analysis, log consolidation, user activity surveillance, and file integrity monitoring. Additional features include event correlation, forensic analysis of logs, and retention of log data. With its robust capabilities, real-time alerts can be generated, enhancing security response. By utilizing Manage Engine's EventLog Analyzer, users can effectively thwart data breaches, uncover the underlying causes of security challenges, and counteract complex cyber threats while ensuring compliance and maintaining a secure operational environment.
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FastBoundSince its inception in 2010, FastBound has successfully handled over one billion transactions through its Electronic A&D and Electronic 4473 FFL software, serving countless Federal Firearms Licensees (FFLs). Rather than diversifying into many areas, FastBound has honed its focus on becoming a leader in firearms compliance software. The company's deep expertise and attentive customer support are key factors that lead software companies to prefer FastBound over any other provider for their firearms compliance needs. FastBound boasts a powerful API that integrates seamlessly with an expanding array of point of sale (POS), enterprise resource planning (ERP), and various other software solutions. Additionally, it offers a compliance guarantee backed by legal expertise, ensuring peace of mind for its users. Proudly developed and supported entirely within the United States, FastBound continues to set the standard for excellence in its niche market. The commitment to quality and customer satisfaction further reinforces its reputation as a trusted partner in the firearms industry.
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StackAIStackAI is an enterprise AI automation platform built to help organizations create end-to-end internal tools and processes with AI agents. Unlike point solutions or one-off chatbots, StackAI provides a single platform where enterprises can design, deploy, and govern AI workflows in a secure, compliant, and fully controlled environment. Using its visual workflow builder, teams can map entire processes — from data intake and enrichment to decision-making, reporting, and audit trails. Enterprise knowledge bases such as SharePoint, Confluence, Notion, Google Drive, and internal databases can be connected directly, with features for version control, citations, and permissioning to keep information reliable and protected. AI agents can be deployed in multiple ways: as a chat assistant embedded in daily workflows, an advanced form for structured document-heavy tasks, or an API endpoint connected into existing tools. StackAI integrates natively with Slack, Teams, Salesforce, HubSpot, ServiceNow, Airtable, and more. Security and compliance are embedded at every layer. The platform supports SSO (Okta, Azure AD, Google), role-based access control, audit logs, data residency, and PII masking. Enterprises can monitor usage, apply cost controls, and test workflows with guardrails and evaluations before production. StackAI also offers flexible model routing, enabling teams to choose between OpenAI, Anthropic, Google, or local LLMs, with advanced settings to fine-tune parameters and ensure consistent, accurate outputs. A growing template library speeds deployment with pre-built solutions for Contract Analysis, Support Desk Automation, RFP Response, Investment Memo Generation, and InfoSec Questionnaires. By replacing fragmented processes with secure, AI-driven workflows, StackAI helps enterprises cut manual work, accelerate decision-making, and empower non-technical teams to build automation that scales across the organization.
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QuantA cloud-based solution designed for managing retail spaces, product categories, and planograms is now available. It features intelligent automation that generates planograms based on sales data, ensuring that planograms remain up-to-date even across extensive retail networks with multiple locations. Quant serves as a comprehensive tool for Space Planning and Category Management, including functionalities for planograms, product ranging, shelf labels, POS printing, in-store communication, and marketing. Leveraging the advantages of cloud computing, Quant Cloud enables teams to collaborate on projects from anywhere in the world, accessing the same database seamlessly across various devices. There’s no requirement for complex infrastructure setups or additional strain on your IT resources. Our team of consultants is readily available to provide support, training your staff and facilitating data integration, allowing Quant to be operational in under 12 weeks. This efficient onboarding process means you can quickly start reaping the benefits of improved retail management.
What is Graph Engine?
Graph Engine (GE) is an advanced distributed in-memory data processing platform that utilizes a strongly-typed RAM storage system combined with a flexible distributed computation engine. This RAM storage operates as a high-performance key-value store, which can be accessed throughout a cluster of machines, enabling efficient data retrieval. By harnessing the power of this RAM store, GE allows for quick random data access across vast distributed datasets, making it particularly effective for handling large graphs. Its capacity to conduct fast data exploration and perform distributed parallel computations makes GE a prime choice for processing extensive datasets, specifically those with billions of nodes. The engine adeptly supports both low-latency online query processing and high-throughput offline analytics, showcasing its versatility in dealing with massive graph structures. The significance of schema in efficient data processing is highlighted by the necessity of strongly-typed data models, which are crucial for optimizing storage and accelerating data retrieval while maintaining clear data semantics. GE stands out in managing billions of runtime objects, irrespective of their sizes, and it operates with exceptional efficiency. Even slight fluctuations in the number of objects can greatly affect performance, emphasizing that every byte matters. Furthermore, GE excels in rapid memory allocation and reallocation, leading to impressive memory utilization ratios that significantly bolster its performance. This combination of capabilities positions GE as an essential asset for developers and data scientists who are navigating the complexities of large-scale data environments, enabling them to derive valuable insights from their data with ease.
What is Grakn?
The cornerstone of developing intelligent systems is the database, with Grakn exemplifying a highly advanced knowledge graph database. It boasts a remarkably intuitive and expressive data schema, enabling the creation of hierarchies, hyper-entities, hyper-relations, and rules for constructing comprehensive knowledge models. Grakn employs an intelligent language that performs logical inferences on various data types, relationships, attributes, and complex patterns in real-time across both distributed and stored data. Additionally, it includes integrated distributed analytics algorithms, such as Pregel and MapReduce, which users can easily access through simple queries within the language. The system abstracts low-level patterns effectively, making it easier to articulate intricate constructs while ensuring that query execution is optimized automatically. By utilizing Grakn KGMS and Workbase, businesses can efficiently expand their knowledge graphs. Moreover, this distributed database is designed to operate optimally across a network of computers by employing strategies like partitioning and replication, which guarantees consistent scalability and performance. Ultimately, Grakn not only streamlines the management of complex data but also enhances the overall capability of intelligent systems.
Integrations Supported
Amazon Web Services (AWS)
Google Cloud Platform
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Microsoft
Date Founded
1975
Company Location
United States
Company Website
www.graphengine.io
Company Facts
Organization Name
Grakn Labs
Date Founded
2016
Company Website
grakn.ai/