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DBMS > CockroachDB vs. Drizzle vs. Geode vs. HEAVY.AI vs. Kinetica

System Properties Comparison CockroachDB vs. Drizzle vs. Geode vs. HEAVY.AI vs. Kinetica

Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonDrizzle  Xexclude from comparisonGeode  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonKinetica  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score1.92
Rank#131  Overall
#23  Key-value stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websitewww.cockroachlabs.comgeode.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
www.kinetica.com
Technical documentationwww.cockroachlabs.com/­docsgeode.apache.org/­docsdocs.heavy.aidocs.kinetica.com
DeveloperCockroach LabsDrizzle project, originally started by Brian AkerOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.HEAVY.AI, Inc.Kinetica
Initial release20152008200220162012
Current release23.1.1, May 20237.2.4, September 20121.1, February 20175.10, January 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availableOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses available as GemfireOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++JavaC++ and CUDAC, C++
Server operating systemsLinux
macOS
Windows
FreeBSD
Linux
OS X
All OS with a Java VM infothe JDK (8 or later) is also requiredLinuxLinux
Data schemedynamic schemayesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nononono
Secondary indexesyesyesnonoyes
SQL infoSupport of SQLyes, wire compatible with PostgreSQLyes infowith proprietary extensionsSQL-like query language (OQL)yesSQL-like DML and DDL statements
APIs and other access methodsJDBCJDBCJava Client API
Memcached protocol
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C
C++
Java
PHP
.Net
All JVM based languages
C++
Groovy
Java
Scala
All languages supporting JDBC/ODBC/Thrift
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonouser defined functionsnouser defined functions
Triggersnono infohooks for callbacks inside the server can be used.yes infoCache Event Listenersnoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingShardingSharding infoRound robinSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTMulti-source replication
Source-replica replication
Multi-source replicationMulti-source replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDyes, on a single nodenono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlRole-based access controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights per client and object definablefine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
CockroachDBDrizzleGeodeHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Kinetica
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