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DBMS > GridDB vs. Hawkular Metrics vs. Sadas Engine vs. TimescaleDB vs. Tkrzw

System Properties Comparison GridDB vs. Hawkular Metrics vs. Sadas Engine vs. TimescaleDB vs. Tkrzw

Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSadas Engine  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSTime Series DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score0.00
Rank#385  Overall
#159  Relational DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
Websitegriddb.netwww.hawkular.orgwww.sadasengine.comwww.timescale.comdbmx.net/­tkrzw
Technical documentationdocs.griddb.netwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.timescale.com
DeveloperToshiba CorporationCommunity supported by Red HatSADAS s.r.l.TimescaleMikio Hirabayashi
Initial release20132014200620172020
Current release5.1, August 20228.02.15.0, May 20240.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0commercial infofree trial version availableOpen Source infoApache 2.0Open Source infoApache Version 2.0
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 languageC++JavaC++CC++
Server operating systemsLinuxLinux
OS X
Windows
AIX
Linux
Windows
Linux
OS X
Windows
Linux
macOS
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesno
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.nononoyesno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noyesyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP RESTJDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
Python
Ruby
.Net
C
C#
C++
Groovy
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnononouser 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 Alertingnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrahorizontal partitioningyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on CassandranoneSource-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACID
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.yesnoyes infomanaged by 'Learn by Usage'noyes infousing specific database classes
User concepts infoAccess controlAccess rights for users can be defined per databasenoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
GridDBHawkular MetricsSadas EngineTimescaleDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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