Basic Introduction to Crate @ ViennaDB Meetup
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Crate is a fully sharded, distributed SQL database designed for real-time search and aggregation to support scalable applications. It features a simple installation and operation process with support for diverse data types and horizontal scalability. Crate excels in use cases involving real-time analytics and high-volume, semi-structured data but is not suited for scenarios requiring strong transactional consistency.
Basic Introduction to Crate @ ViennaDB Meetup
- 1. Put Data to Work. Simply. An Introduction to Crate Johannes Moser, Head of Integrations
- 2. About Me • Loves working with people and code • Head of Integrations at @CrateIO johannes@crate.io @joemoeAT
- 3. Put DATA TO WORK. SIMPLY Crate is a fully sharded, distributed, horizontally scaling SQL database with realtime search and aggregation to build worry-free applications and services at scale. super simple to use & operate plays well with others delivers fast results
- 4. Crate is... • distributed standard SQL • shared nothing architecture • auto-sharding/partioning/replication • extremely simple to install/operate • all data (relational, json docs, blobs) • realtime search & aggregations • horizontal scaling, elastic, resilient • dynamic schemas, agile dev • eventual consistent, atomic on doc level • balanced memory-disk usage • ideal for containers
- 5. Crate - Stateful Container enabled through masterless shared nothing architecture crate APP CONTAINERS LOCAL STORAGE crate APP CONTAINERS LOCAL STORAGE crate APP CONTAINERS LOCAL STORAGE crate APP CONTAINERS LOCAL STORAGE CR ATE CLUSTE R CR ATE Container CLUSTER Cr ate is like an et h er - an omnipresent, pe rsistent layer for your data
- 6. Crate Clusters running right now (ca 400)
- 7. Competition • MySQL • lacks scalability, fault-tolerance, search • Hadoop World • it´s never realtime and not hot data • Cassandra • rather inflexible, complex indexing, fat stack • Elasticsearch • no SQL, not a DB, no compute of result • MemSQL • memory only really, closed source • MongoDB • slow aggregations, lack of search, tough scaling • traditional, proprietary SQL servers • lack of scaling, complex and $$$
- 8. Customer “Skyhigh Networks” • Security Events (times series) • Realtime Dashboard • side-by-side to Hadoop cluster • 500 customers running on Crate • better spread of data & load & resilience • 3,2 BN inserts/updates per day • 48.000 concurrent TCP connections • about 60 nodes on AWS • 100% drop-in for MySQL cluster -75% servers, but 20x performance
- 9. Use Cases for crate Well Suited • Real time analytics and business intelligence, Dashboards • Internet of Things backend • High volume, semistructured/ dynamic data • Operational database for web applications at scale • Combination of operational DB and analytics DB Not Well Suited • Systems that require strong transactional consistency • Strong, complex relational data (e.g insurances…)
- 10. DEMO
- 11. Crate Components ( Crate Elasticsearch , other Open Source) Crate OPEN SOURCE STACK
- 12. Benefits FOR developerS • run faster ! • use SQL and ORMs • migrate easily from existing solutions • native search & text processing • combine all data (relational, documents, blobs) in one store • schema changes any time without penalty • times series and geospatial support • run Crate on your notebook • deploy app & database together (with Docker) Ruby
- 13. Benefits OPS • horizontally scalable, elastic • high availability out of the box • ease of use, simple operation • massively parallel read & write • incremental backup & restore • on prem & cloud integrations & containers • manage TB-clusters for realtime queries • available for Linux, Mac, Windows • run in containers: Docker, CoreOS, Tutum, Containership
- 14. THANK YOU Johannes Moser, Head of Integrations @joemoeAT, johannes@crate.io