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DBMS > Apache IoTDB vs. PostgreSQL vs. Sphinx vs. SQLite vs. Vertica

System Properties Comparison Apache IoTDB vs. PostgreSQL vs. Sphinx vs. SQLite vs. Vertica

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSphinx  Xexclude from comparisonSQLite  Xexclude from comparisonVertica infoOpenText™ Vertica™  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 databasesWidely used embeddable, in-process RDBMSCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
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 DBMSRelational DBMS infoColumn oriented
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score114.32
Rank#10  Overall
#7  Relational DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Websiteiotdb.apache.orgwww.postgresql.orgsphinxsearch.comwww.sqlite.orgwww.vertica.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgresql.org/­docssphinxsearch.com/­docswww.sqlite.org/­docs.htmlvertica.com/­documentation
DeveloperApache Software FoundationPostgreSQL Global Development Group infowww.postgresql.org/­developerSphinx Technologies Inc.Dwayne Richard HippOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20181989 info1989: Postgres, 1996: PostgreSQL200120002005
Current release1.1.0, April 202316.3, May 20243.5.1, February 20233.46.0  (23 May 2024), May 202412.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSDOpen Source infoGPL version 2, commercial licence availableOpen Source infoPublic Domaincommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC++CC++
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
server-lessLinux
Data schemeyesyesyesyes infodynamic column typesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyesnoyes infonot rigid because of 'dynamic typing' concept.yes
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.nono
Secondary indexesyesyesyes infofull-text index on all search fieldsyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageyes infostandard with numerous extensionsSQL-like query language (SphinxQL)yes infoSQL-92 is not fully supportedFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocolADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
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
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesyesnoyesyes, called Custom Alerts
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 supportednonehorizontal partitioning, hierarchical 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 extensionsnonenoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknononono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infovia file-system locksyes
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.yesnoyesno
User concepts infoAccess controlyesfine grained access rights according to SQL-standardnonofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache IoTDBPostgreSQLSphinxSQLiteVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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Apache IoTDBPostgreSQLSphinxSQLiteVertica infoOpenText™ Vertica™
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