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DBMS > Apache IoTDB vs. RocksDB vs. TimescaleDB vs. Trino

System Properties Comparison Apache IoTDB vs. RocksDB vs. TimescaleDB vs. Trino

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonRocksDB  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTrino  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 FlinkEmbeddable persistent key-value store optimized for fast storage (flash and RAM)A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelTime Series DBMSKey-value storeTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#159  Overall
#14  Time Series DBMS
Score2.84
Rank#97  Overall
#16  Key-value stores
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Score5.28
Rank#61  Overall
#35  Relational DBMS
Websiteiotdb.apache.orgrocksdb.orgwww.timescale.comtrino.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgithub.com/­facebook/­rocksdb/­wikidocs.timescale.comtrino.io/­broadcast
trino.io/­docs/­current
DeveloperApache Software FoundationFacebook, Inc.TimescaleTrino Software Foundation
Initial release2018201320172012 info2020 rebranded from PrestoSQL
Current release1.1.0, April 20239.4.0, June 20242.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoBSDOpen Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++CJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxLinux
OS X
Windows
Linux
macOS infofor devlopment
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data 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.nonoyesno
Secondary indexesyesnoyesdepending on connected data-source
SQL infoSupport of SQLSQL-like query languagenoyes infofull PostgreSQL SQL syntaxyes
APIs and other access methodsJDBC
Native API
C++ API
Java API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
RESTful HTTP API
Trino CLI
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C++
Go
Java
Perl
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresyesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes, depending on connected data-source
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningyes, across time and space (hash partitioning) attributesdepending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesSource-replica replication with hot standby and reads on replicas infodepending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate Consistencydepending on connected data-source
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDdepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesdepending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesnofine grained access rights according to SQL-standardSQL standard access control
More information provided by the system vendor
Apache IoTDBRocksDBTimescaleDBTrino
News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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More resources
Apache IoTDBRocksDBTimescaleDBTrino
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