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DBMS > Amazon Aurora vs. Apache IoTDB vs. PostgreSQL vs. QuestDB vs. Sphinx

System Properties Comparison Amazon Aurora vs. Apache IoTDB vs. PostgreSQL vs. QuestDB vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache IoTDB  Xexclude from comparisonPostgreSQL  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAn 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 SQLA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSTime Series DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Time Series DBMSSearch engine
Secondary database modelsDocument storeDocument 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
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­rds/­auroraiotdb.apache.orgwww.postgresql.orgquestdb.iosphinxsearch.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmliotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.postgresql.org/­docsquestdb.io/­docssphinxsearch.com/­docs
DeveloperAmazonApache Software FoundationPostgreSQL Global Development Group infowww.postgresql.org/­developerQuestDB Technology IncSphinx Technologies Inc.
Initial release201520181989 info1989: Postgres, 1996: PostgreSQL20142001
Current release1.1.0, April 202316.3, May 20243.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoBSDOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCJava (Zero-GC), C++, RustC++
Server operating systemshostedAll OS with a Java VM (>= 1.8)FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyes infoschema-free via InfluxDB Line Protocolyes
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.yesnoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLyesSQL-like query languageyes infostandard with numerous extensionsSQL with time-series extensionsSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
Native API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C
C#
C++
Go
Java
Python
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyesyesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersyesyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioninghorizontal partitioning (by time range) + vertical partitioning (by deviceId)partitioning by range, list and (since PostgreSQL 11) by hashhorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replication infoother methods possible by using 3rd party extensionsSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID for single-table writesno
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.yesyesnoyes infothrough memory mapped files
User concepts infoAccess controlfine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standardno
More information provided by the system vendor
Amazon AuroraApache IoTDBPostgreSQLQuestDBSphinx
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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