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DBMS > CrateDB vs. EXASOL vs. Splice Machine

System Properties Comparison CrateDB vs. EXASOL vs. Splice Machine

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEXASOL  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionDistributed Database based on LuceneHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#229  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websitecratedb.comwww.exasol.comsplicemachine.com
Technical documentationcratedb.com/­docswww.exasol.com/­resourcessplicemachine.com/­how-it-works
DeveloperCrateExasolSplice Machine
Initial release201320002014
Current release3.1, March 2021
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJava
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nono
Secondary indexesyesyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesyes
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
JDBC
Native Spark Datasource
ODBC
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Java
Lua
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions (Javascript)user defined functionsyes infoJava
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlrights management via user accountsAccess rights for users, groups and roles according to SQL-standardAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
CrateDBEXASOLSplice Machine
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
CrateDBEXASOLSplice Machine
Recent citations in the news

CrateDB Announces Availability of CrateDB on Google Cloud Marketplace
8 April 2024, Datanami

CrateDB Appoints Sergey Gerasimenko as New CTO
19 February 2024, PR Newswire

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How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
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20 March 2024, businesswire.com

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Exasol Reimagines In-Memory Analytics with Major Database Update
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26 August 2021, The Register

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