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DBMS > Apache IoTDB vs. PostgreSQL vs. Sphinx vs. SQream DB vs. SurrealDB

System Properties Comparison Apache IoTDB vs. PostgreSQL vs. Sphinx vs. SQream DB vs. SurrealDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSphinx  Xexclude from comparisonSQream DB  Xexclude from comparisonSurrealDB  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 FlinkWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLOpen source search engine for searching in data from different sources, e.g. relational databasesa GPU-based, columnar RDBMS for big data analytics workloadsA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelTime Series DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Search engineRelational DBMSDocument store
Graph DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.74
Rank#224  Overall
#103  Relational DBMS
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Websiteiotdb.apache.orgwww.postgresql.orgsphinxsearch.comsqream.comsurrealdb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgresql.org/­docssphinxsearch.com/­docsdocs.sqream.comsurrealdb.com/­docs
DeveloperApache Software FoundationPostgreSQL Global Development Group infowww.postgresql.org/­developerSphinx Technologies Inc.SQream TechnologiesSurrealDB Ltd
Initial release20181989 info1989: Postgres, 1996: PostgreSQL200120172022
Current release1.1.0, April 202316.3, May 20243.5.1, February 20232022.1.6, December 2022v1.5.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSDOpen Source infoGPL version 2, commercial licence availablecommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++C++, CUDA, Haskell, Java, ScalaRust
Server operating systemsAll OS with a Java VM (>= 1.8)FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
LinuxLinux
macOS
Windows
Data schemeyesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesnoyes, ANSI Standard SQL Typesyes
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.noyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL-like query languageyes infostandard with numerous extensionsSQL-like query language (SphinxQL)yesSQL-like query language
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol.Net
JDBC
ODBC
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
JavaScript (Node.js)
Python
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nouser defined functions in Python
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)partitioning by range, list and (since PostgreSQL 11) by hashSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication infoother methods possible by using 3rd party extensionsnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnoyes, based on authentication and database rules

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More resources
Apache IoTDBPostgreSQLSphinxSQream DBSurrealDB
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