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DBMS > Datomic vs. mSQL vs. ObjectBox vs. Sphinx vs. Splice Machine

System Properties Comparison Datomic vs. mSQL vs. ObjectBox vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonObjectBox  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitymSQL (Mini SQL) is a simple and lightweight RDBMSExtremely 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 DBMSRelational DBMSObject oriented DBMSSearch engineRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.datomic.comhughestech.com.au/­products/­msqlobjectbox.iosphinxsearch.comsplicemachine.com
Technical documentationdocs.datomic.comdocs.objectbox.iosphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperCognitectHughes TechnologiesObjectBox LimitedSphinx Technologies Inc.Splice Machine
Initial release20121994201720012014
Current release1.0.6735, June 20234.4, October 20213.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infofree licenses can be providedOpen 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 servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureCC and C++C++Java
Server operating systemsAll OS with a Java VMAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Android
iOS
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonono
Secondary indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersnoSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Proprietary native APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
C
C++
Delphi
Java
Perl
PHP
Tcl
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 proceduresyes infoTransaction Functionsnononoyes infoJava
TriggersBy using transaction functionsnononoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnonenoneSharding 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 nodesnone infoBut extensive use of caching in the application peersnoneonline/offline synchronization between client and servernoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesnoyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes 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.yes inforecommended only for testing and developmentnonoyes
User concepts infoAccess controlnonoyesnoAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
DatomicmSQL infoMini SQLObjectBoxSphinxSplice Machine
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