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

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

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonRavenDB  Xexclude from comparisonTimescaleDB  Xexclude from comparisonYDB  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 Operational and Transactional Enterprise NoSQL Document DatabaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA 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 DBMSDocument storeTime Series DBMSDocument store
Relational DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
Relational 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
Score2.92
Rank#101  Overall
#18  Document stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websiteiotdb.apache.orgwww.hawkular.orgravendb.netwww.timescale.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guideravendb.net/­docsdocs.timescale.comydb.tech/­en/­docs
DeveloperApache Software FoundationCommunity supported by Red HatHibernating RhinosTimescaleYandex
Initial release20182014201020172019
Current release1.1.0, April 20235.4, July 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPL version 3, commercial license availableOpen Source infoApache 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC#C
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
OS X
Windows
Linux
Data schemeyesschema-freeschema-freeyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesnonumerics, 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 indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenoSQL-like query language (RQL)yes infofull PostgreSQL SQL syntaxSQL-like query language (YQL)
APIs and other access methodsJDBC
Native API
HTTP REST.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API (DynamoDB compatible)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
Python
Ruby
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyesnoyesuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
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 CassandraShardingyes, 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 replicationSource-replica replication with hot standby and reads on replicas infoActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyesnono
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
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID, Cluster-wide transaction availableACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.yesnonono
User concepts infoAccess controlyesnoAuthorization levels configured per client per databasefine grained access rights according to SQL-standardAccess rights defined for Yandex Cloud users

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More resources
Apache IoTDBHawkular MetricsRavenDBTimescaleDBYDB
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