Language of your choice and use it for in-database analytics. Lua, Exasol allows you to integrate the analytics programming Schemas” as well as a high performance data integrationįramework, you can connect to and analyze data fromĪdvanced in-database analytics - Alongside out-of-the-box support for R, Python, Java and Perform high-speed analytics against structured andįaster access to more data sources - Through a data virtualization framework called “virtual Supports all native HDFS formats enabling you to Hadoop integration has never been so easy.
Minimize any data administration overhead. Self-tuning tasks automatically, which optimize performance and Self-tuning - Intelligent algorithms monitor usage and perform Increase performance by adding additional nodes. Scalability - Linear scalability lets you to extend your system and High user concurrency - Thousands of users can simultaneously access and analyze largeĪmounts of data without compromising query performance. That process data locally in each node’s main memory. Queries are distributed acrossĪll nodes in a cluster using optimized, parallel algorithms
Massively Parallel Processing (MPP) - Exasol was developed as a parallel system based on a Main memory and accelerates analytical performance. I/O operations and amount of data needed for processing in Of data to be processed in the main memory for dramaticallyĬolumn-based storage and compression - Columnar storage and compression reduces the number of In-memory technology - Innovative in-memory algorithms enable large amounts The image below provides you with a high-level overview of Exasol and it's features.Įxasol database consists of the following key features: Your BI and reporting, and to turn data into value.
Volumes of data faster than ever before, helping you to accelerate From business-critical dataĪpplications to advanced analytics, Exasol helps you analyze large
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See individual Java ORM or driver for data access support level.Exasol is the high-performance, in-memory MPP(Massively Parallel Processing) database See individual Java ORM or driver for data access version support. (includes client-side transaction retry handling)īuild a Node.js App with CockroachDB (pg)īuild a Python App with CockroachDB (psycopg2)ĭata access frameworks (e.g., ORMs) Languageīuild a Go App with CockroachDB (upper/db)īuild a Java App with CockroachDB (Hibernate)īuild a Spring App with CockroachDB (MyBatis)īuild a Node.js App with CockroachDB (Sequelize)īuild a Node.js App with CockroachDB (Knex.js)īuild a TypeScript App with CockroachDB (TypeORM)īuild a Ruby App with CockroachDB (ActiveRecord)īuild a Python App with CockroachDB (Django)īuild a Python App with CockroachDB (PonyORM)īuild a Python App with CockroachDB (SQLAlchemy) (use latest version of CockroachDB adapter) If you encounter problems using CockroachDB with any of the tools listed on this page, please open an issue with details to help us make progress toward better support.įor a list of tools supported by the CockroachDB community, see Third-Party Tools Supported by the Community. For client-side transaction retry handling samples, see Example Apps. Unless explicitly stated, support for a driver or data access framework does not include automatic, client-side transaction retry handling.
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The primary features of the tool are compatible with CockroachDB (e.g., connecting and basic database operations), but full integration may require additional steps, lack support for all features, or exhibit unexpected behavior.
Cockroach Labs guarantees official support for a set of popular PostgreSQL tools, which we list on this page. CockroachDB's support of the PostgreSQL wire protocol makes most PostgreSQL drivers, ORM frameworks, and other types of third-party database tools designed for PostgreSQL compatible with CockroachDB.