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DBMS > Apache Druid vs. Apache IoTDB vs. Postgres-XL vs. Sphinx

System Properties Comparison Apache Druid vs. Apache IoTDB vs. Postgres-XL vs. Sphinx

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonApache IoTDB  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMS
Time Series DBMS
Time Series DBMSRelational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitedruid.apache.orgiotdb.apache.orgwww.postgres-xl.orgsphinxsearch.com
Technical documentationdruid.apache.org/­docs/­latest/­designiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgres-xl.org/­documentationsphinxsearch.com/­docs
DeveloperApache Software Foundation and contributorsApache Software FoundationSphinx Technologies Inc.
Initial release201220182014 infosince 2012, originally named StormDB2001
Current release29.0.1, April 20241.1.0, April 202310 R1, October 20183.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache license v2Open Source infoApache Version 2.0Open Source infoMozilla public licenseOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCC++
Server operating systemsLinux
OS X
Unix
All OS with a Java VM (>= 1.8)Linux
macOS
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyes infoschema-less columns are supportedyesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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.nonoyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL for queryingSQL-like query languageyes infodistributed, parallel query executionSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
RESTful HTTP/JSON API
JDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyesuser defined functionsno
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedhorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoMVCCno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemyesfine grained access rights according to SQL-standardno

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More resources
Apache DruidApache IoTDBPostgres-XLSphinx
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