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DBMS > Apache IoTDB vs. GridGain vs. Postgres-XL vs. Quasardb vs. Sphinx

System Properties Comparison Apache IoTDB vs. GridGain vs. Postgres-XL vs. Quasardb vs. Sphinx

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonGridGain  Xexclude from comparisonPostgres-XL  Xexclude from comparisonQuasardb  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkGridGain is an in-memory computing platform, built on Apache IgniteBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresDistributed, high-performance timeseries databaseOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Relational DBMSTime Series DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteiotdb.apache.orgwww.gridgain.comwww.postgres-xl.orgquasar.aisphinxsearch.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.gridgain.com/­docs/­index.htmlwww.postgres-xl.org/­documentationdoc.quasar.ai/­mastersphinxsearch.com/­docs
DeveloperApache Software FoundationGridGain Systems, Inc.quasardbSphinx Technologies Inc.
Initial release201820072014 infosince 2012, originally named StormDB20092001
Current release1.1.0, April 2023GridGain 8.5.110 R1, October 20183.14.1, January 20243.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoMozilla public licensecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen 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 languageJavaJava, C++, .NetCC++C++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Solaris
Windows
Linux
macOS
BSD
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binaryno
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.noyesyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyes infowith tagsyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLyes infodistributed, parallel query executionSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
Native API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP APIProprietary protocol
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)user defined functionsnono
Triggersyesyes (cache interceptors and events)yesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Shardinghorizontal partitioningSharding infoconsistent hashingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes (replicated cache)Source-replica replication with selectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyes (compute grid and hadoop accelerator)nowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoMVCCACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDByes 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.yesyesnoyes infoTransient mode
User concepts infoAccess controlyesSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trailno

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More resources
Apache IoTDBGridGainPostgres-XLQuasardbSphinx
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