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DBMS > Pinecone vs. Realm vs. Sphinx vs. Splice Machine

System Properties Comparison Pinecone vs. Realm vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NamePinecone  Xexclude from comparisonRealm  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA managed, cloud-native vector databaseA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen 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 modelVector DBMSDocument storeSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.16
Rank#95  Overall
#2  Vector DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.pinecone.iorealm.iosphinxsearch.comsplicemachine.com
Technical documentationdocs.pinecone.io/­docs/­overviewrealm.io/­docssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperPinecone Systems, IncRealm, acquired by MongoDB in May 2019Sphinx Technologies Inc.Splice Machine
Initial release2019201420012014
Current release3.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedAndroid
Backend: server-less
iOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateString, Number, Booleanyesnoyes
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 indexesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnonoSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP APIProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesPython.Net
Java infowith Android only
Objective-C
React Native
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 proceduresno inforuns within the applications so server-side scripts are unnecessarynoyes infoJava
Triggersyes infoChange Listenersnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding 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 nodesnonenoneMulti-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 systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, 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.noyes infoIn-Memory realmyes
User concepts infoAccess controlyesnoAccess rights for users, groups and roles according to SQL-standard

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PineconeRealmSphinxSplice Machine
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