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DBMS > Amazon DocumentDB vs. Apache IoTDB vs. PostgreSQL vs. SpatiaLite vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Apache IoTDB vs. PostgreSQL vs. SpatiaLite vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonApache IoTDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpatiaLite  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceAn 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 SQLSpatial extension of SQLiteOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeTime Series DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Spatial DBMSSearch engine
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score1.60
Rank#149  Overall
#3  Spatial DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbiotdb.apache.orgwww.postgresql.orgwww.gaia-gis.it/­fossil/­libspatialite/­indexsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourcesiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgresql.org/­docswww.gaia-gis.it/­gaia-sins/­spatialite_topics.htmlsphinxsearch.com/­docs
DeveloperApache Software FoundationPostgreSQL Global Development Group infowww.postgresql.org/­developerAlessandro FurieriSphinx Technologies Inc.
Initial release201920181989 info1989: Postgres, 1996: PostgreSQL20082001
Current release1.1.0, April 202316.3, May 20245.0.0, August 20203.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoBSDOpen Source infoMPL 1.1, GPL v2.0 or LGPL v2.1Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
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Implementation languageJavaCC++C++
Server operating systemshostedAll OS with a Java VM (>= 1.8)FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
server-lessFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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 infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageyes infostandard with numerous extensionsyesSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C
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
Server-side scripts infoStored proceduresnoyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersnoyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesnonehorizontal partitioning (by time range) + vertical partitioning (by deviceId)partitioning by range, list and (since PostgreSQL 11) by hashnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable 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 methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Integration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.yesnoyes
User concepts infoAccess controlAccess rights for users and rolesyesfine grained access rights according to SQL-standardnono

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More resources
Amazon DocumentDBApache IoTDBPostgreSQLSpatiaLiteSphinx
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