Crate.io today announced general availability of CrateDB 1.0, an open source SQL database that enables real-time analytics for machine data applications. CrateDB makes machine data applications that were previously only possible using NoSQL solutions available to mainstream SQL developers. The company also announced today that it has opened a new world headquarters in San Francisco, adding to its existing presence in Berlin, Germany and Dornbirn, Austria.
“The growth of machine data and the opportunities that businesses have to capitalize on it are outstripping the ability of their data management infrastructure to act on it,” said Jason Stamper, Analyst, Data Platforms and Analytics at 451 Research. “CrateDB’s power lies in its ability to enable users to collect and analyze vast amounts of data in real-time, using SQL commands they already know.”
Downloaded more than one million times since its introduction in 2014, CrateDB combines the familiarity of SQL with the versatility of search and the ease of scalability of containers. It provides an alternative to existing analytic datastores including Splunk.
CrateDB’s unique capabilities are enabled by the following innovations:
- Distributed SQL query engine for faster JOINs, aggregations, and ad-hoc queries
Columnar field caches and a fully distributed query planner enable CrateDB to perform complex queries in real time and overcome many of the performance and flexibility limitations of first-generation distributed SQL databases.
- SQL with integrated search for data and query versatility
CrateDB is a unique combination of SQL and search technology, which enables a wide range of analytics, including machine learning and predictive analytics, on time series, full text, JSON, geospatial, and other structured and unstructured data without having to use different database engines to do so.
- Container architecture and automatic data sharding for simple scaling
Database scalability is vital for handling variations in machine data volume, but this is normally difficult to do. CrateDB can run as a cluster of containers, which enables it to be scaled easily with Docker, Kubernetes, or Mesos container platforms. In addition, CrateDB automatically shards and redistributes data across the cluster as it changes size to optimize performance and high availability.
“When we founded Crate.io, we set out to reinvent SQL for the machine data era. Today, 75 percent of our customers use CrateDB to manage machine and IoT data because of its superior ease of use, performance, and versatility,” said Christian Lutz, CEO of Crate.io. “The general availability of the product and our expansion to San Francisco mark a new phase in our growth, and we look forward to driving further innovation of the platform both internally and by extension through the open source community.”
Customer Testimonials for CrateDB
“The mission-criticality of our industrial sensor and data acquisition devices cannot be overstated. Our well known key customers in the automotive, energy, aerospace and civil engineering segment rely on our ability to take synchronized and decentral measurements from hundreds of thousands of sensors, feed them into a database and extract that data for instant visibility of power, temperature, pressure, speed and torque. Based on the real-time aggregated meta-data they make their decisions. CrateDB is the only database that gives us the speed, scalability and ease of use that our teams, customers and applications require.”
– Juergen Sutterlueti, Head of Energy Segment, Gantner Instruments
“More than 40 percent of the Fortune 500 customers depend on Skyhigh to help address their cloud security needs. CrateDB is an important part of our data stack giving us the performance and horizontal scalability to meet our rapidly growing business needs.”
– Sekhar Sarukkai, co-founder, chief scientist and VP of engineering, Skyhigh Networks
“At Space-Time Insight we create Industrial Internet of Things solutions to help our customers extend asset life, predict maintenance needs, and optimize logistics and operations. We make extensive use of machine learning and streaming analytics, and CrateDB is particularly well-suited for the geospatial and temporal data we work with, including support for distributed joins. It allows us to write and query sensor data at more than 200,000 rows per second, and query terabytes of data.”
– Paul Hofmann, CTO, Space-Time Insight
New in CrateDB 1.0
The newest release of CrateDB includes improvements in performance, ease of use, and SQL completeness:
- Support for outer JOINs and sub-queries
- Conditional and trigonometric functions
- Schema and metadata discovery interfaces
- Faster INSERT performance
- Read-only nodes
- Support for the PostgreSQL wire protocol for easier integration