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DBMS > Graph Engine vs. IRONdb vs. TimescaleDB vs. Tkrzw

System Properties Comparison Graph Engine vs. IRONdb vs. TimescaleDB vs. Tkrzw

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonIRONdb  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityA 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 modelGraph DBMS
Key-value store
Time Series DBMSTime Series DBMSKey-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.67
Rank#232  Overall
#21  Graph DBMS
#34  Key-value stores
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websitewww.graphengine.iowww.circonus.com/solutions/time-series-database/www.timescale.comdbmx.net/­tkrzw
Technical documentationwww.graphengine.io/­docs/­manualdocs.circonus.com/irondb/category/getting-starteddocs.timescale.com
DeveloperMicrosoftCirconus LLC.TimescaleMikio Hirabayashi
Initial release2010201720172020
Current releaseV0.10.20, January 20182.15.0, May 20240.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen 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 language.NET and CC and C++CC++
Server operating systems.NETLinuxLinux
OS X
Windows
Linux
macOS
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsnumerics, 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.nonoyesno
Secondary indexesnoyes
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)yes infofull PostgreSQL SQL syntaxno
APIs and other access methodsRESTful HTTP APIHTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
F#
Visual Basic
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesyes, in Luauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningAutomatic, metric affinity per nodeyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awareSource-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency per node, eventual consistency across nodesImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes infousing specific database classes
User concepts infoAccess controlnofine grained access rights according to SQL-standardno

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More resources
Graph Engine infoformer name: TrinityIRONdbTimescaleDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Recent citations in the news

Trinity
30 October 2010, Microsoft

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22 February 2022, Business Wire

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

provided by Google News



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