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DBMS > CrateDB vs. ObjectBox vs. Sphinx vs. Splice Machine

System Properties Comparison CrateDB vs. ObjectBox vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonObjectBox  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionDistributed Date Store based on LuceneExtremely fast embedded database for small devices, IoT and MobileOpen source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMS
Search engine
Object oriented DBMSSearch engineRelational DBMS
Secondary database modelsDocument storeTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.76
Rank#190  Overall
#93  Relational DBMS
#12  Search engines
Score0.65
Rank#208  Overall
#11  Object oriented DBMS
Score6.47
Rank#59  Overall
#7  Search engines
Score0.79
Rank#186  Overall
#91  Relational DBMS
Websitecrate.ioobjectbox.iosphinxsearch.comsplicemachine.com
Technical documentationcrate.io/­docsdocs.objectbox.iosphinxsearch.com/­docsdoc.splicemachine.com
DeveloperCrateObjectBox LimitedSphinx Technologies Inc.Splice Machine
Initial release2013201720012014
Current release3.2.1, January 20202.0
License infoCommercial or Open SourceOpen SourceOpen Source infoApache License 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC and C++C++Java
Server operating systemsAll OS with a Java 7 (and higher) VMAndroid
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 infofull-text index on all search fieldsyes
SQL infoSupport of SQLyes, but no triggers and constraintsnoSQL-like query language (SphinxQL)yes
APIs and other access methodsADO.NET infocommunity maintained client
JDBC
MQTT (Message Queue Telemetry Transport)
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Proprietary native APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesErlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsnonoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoronline/offline synchronization between client and servernoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read Your Own Writes Consistency infofor primary key lookups
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
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 strategyACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlrights management via user accountsyesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
CrateDBObjectBoxSphinxSplice Machine
Specific characteristicsCrateDB is an open source distributed SQL database that spreads data and processing...
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THE ONLY SCALE-OUT SQL RDBMS WITH BUILT-IN MACHINE LEARNING For data-rich, real-time...
» more
Competitive advantagesCrateDB is typically used in operational analytics applications, particularly those...
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Operational Workloads: Full ACID support with high performance at scale Multi-row...
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Typical application scenariosCrateDB is ideal for integrating and analyzing streams of data--often machine-generated--in...
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New AI/ML and IoT Applications Data Warehouse Offloads Application Modernization...
» more
Key customersCrateDB customers include McAfee, Qualtrics , Nokia, NBC Golfnow , Digital Domain...
» more
Market metricsThe CrateDB open source project was started in 2014. CrateDB was the winner of TechCrunch...
» more
Licensing and pricing modelsCrateDB pricing CrateDB Community Edition is open source and free to use under the...
» more
Kubernetes Community Edition: https://hub.helm.sh/charts/splicemachine/splice-helm...
» more
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