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DBMS > Datomic vs. HugeGraph vs. NSDb vs. RethinkDB vs. Sphinx

System Properties Comparison Datomic vs. HugeGraph vs. NSDb vs. RethinkDB vs. Sphinx

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonHugeGraph  Xexclude from comparisonNSDb  Xexclude from comparisonRethinkDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA fast-speed and highly-scalable Graph DBMSScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesDBMS for the Web with a mechanism to push updated query results to applications in realtime.Open source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSGraph DBMSTime Series DBMSDocument storeSearch engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score2.74
Rank#105  Overall
#19  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.datomic.comgithub.com/­hugegraph
hugegraph.apache.org
nsdb.iorethinkdb.comsphinxsearch.com
Technical documentationdocs.datomic.comhugegraph.apache.org/­docsnsdb.io/­Architecturerethinkdb.com/­docssphinxsearch.com/­docs
DeveloperCognitectBaiduThe Linux Foundation infosince July 2017Sphinx Technologies Inc.
Initial release20122018201720092001
Current release1.0.6735, June 20230.92.4.1, August 20203.5.1, February 2023
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache Version 2Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaJava, ScalaC++C++
Server operating systemsAll OS with a Java VMLinux
macOS
Unix
Linux
macOS
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes: int, bigint, decimal, stringyes infostring, binary, float, bool, date, geometryno
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 indexesyesyes infoalso supports composite index and range indexall fields are automatically indexedyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoSQL-like query languagenoSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP API
TinkerPop Gremlin
gRPC
HTTP REST
WebSocket
Proprietary protocol
Supported programming languagesClojure
Java
Groovy
Java
Python
Java
Scala
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infoTransaction Functionsasynchronous Gremlin script jobsnono
TriggersBy using transaction functionsnoClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding inforange basedSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparknoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC basedyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesUsing Apache Luceneyesyes infoThe original contents of fields are not stored in the Sphinx index.
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 developmentyesno
User concepts infoAccess controlnoUsers, roles and permissionsyes infousers and table-level permissionsno

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More resources
DatomicHugeGraphNSDbRethinkDBSphinx
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