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DBMS > Apache IoTDB vs. Hawkular Metrics vs. Splice Machine vs. TimescaleDB vs. Vitess

System Properties Comparison Apache IoTDB vs. Hawkular Metrics vs. Splice Machine vs. TimescaleDB vs. Vitess

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVitess  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 FlinkHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websiteiotdb.apache.orgwww.hawkular.orgsplicemachine.comwww.timescale.comvitess.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidesplicemachine.com/­how-it-worksdocs.timescale.comvitess.io/­docs
DeveloperApache Software FoundationCommunity supported by Red HatSplice MachineTimescaleThe Linux Foundation, PlanetScale
Initial release20182014201420172013
Current release1.1.0, April 20233.1, March 20212.15.0, May 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJavaCGo
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Docker
Linux
macOS
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, 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.nonoyes
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyesyes infofull PostgreSQL SQL syntaxyes infowith proprietary extensions
APIs and other access methodsJDBC
Native API
HTTP RESTJDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnoyes infoJavauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes infoproprietary syntax
Triggersyesyes infovia Hawkular Alertingyesyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infobased on CassandraShared Nothhing Auto-Sharding, Columnar Partitioningyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas infoMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparknoYes, via Full Spark Integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynonoyesyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesnoyes
User concepts infoAccess controlyesnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
Apache IoTDBHawkular MetricsSplice MachineTimescaleDBVitess
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