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DBMS > Apache IoTDB vs. Hawkular Metrics vs. TimescaleDB vs. Titan vs. YDB

System Properties Comparison Apache IoTDB vs. Hawkular Metrics vs. TimescaleDB vs. Titan vs. YDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTitan  Xexclude from comparisonYDB  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
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.A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTitan is a Graph DBMS optimized for distributed clusters.A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelTime Series DBMSTime Series DBMSTime Series DBMSGraph DBMSDocument store
Relational DBMS
Secondary database modelsRelational 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
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websiteiotdb.apache.orgwww.hawkular.orgwww.timescale.comgithub.com/­thinkaurelius/­titangithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.timescale.comgithub.com/­thinkaurelius/­titan/­wikiydb.tech/­en/­docs
DeveloperApache Software FoundationCommunity supported by Red HatTimescaleAurelius, owned by DataStaxYandex
Initial release20182014201720122019
Current release1.1.0, April 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoApache 2.0Open Source infoApache license, version 2.0Open Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaCJava
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
Linux
OS X
Windows
Linux
OS X
Unix
Windows
Linux
Data schemeyesschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyesyes
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 indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenoyes infofull PostgreSQL SQL syntaxnoSQL-like query language (YQL)
APIs and other access methodsJDBC
Native API
HTTP RESTADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Clojure
Java
Python
Go
Java
JavaScript (Node.js)
PHP
Python
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 shellyesno
Triggersyesyes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)Sharding infobased on Cassandrayes, across time and space (hash partitioning) attributesyes infovia pluggable storage backendsSharding
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 CassandraSource-replica replication with hot standby and reads on replicas infoyesActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyes infovia Faunus, a graph analytics engineno
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 ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyes infoRelationships in graphno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlyesnofine grained access rights according to SQL-standardUser authentification and security via Rexster Graph ServerAccess rights defined for Yandex Cloud users

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More resources
Apache IoTDBHawkular MetricsTimescaleDBTitanYDB
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