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DBMS > Graph Engine vs. MonetDB vs. TimescaleDB vs. Yanza

System Properties Comparison Graph Engine vs. MonetDB vs. TimescaleDB vs. Yanza

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonMonetDB  Xexclude from comparisonTimescaleDB  Xexclude from comparisonYanza  Xexclude from comparison
Yanza 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 relational database management system that stores data in columnsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLTime Series DBMS for IoT Applications
Primary database modelGraph DBMS
Key-value store
Relational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
Relational 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
Score1.72
Rank#141  Overall
#64  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.graphengine.iowww.monetdb.orgwww.timescale.comyanza.com
Technical documentationwww.graphengine.io/­docs/­manualwww.monetdb.org/­Documentationdocs.timescale.com
DeveloperMicrosoftMonetDB BVTimescaleYanza
Initial release2010200420172015
Current releaseDec2023 (11.49), December 20232.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoMozilla Public License 2.0Open Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation language.NET and CCC
Server operating systems.NETFreeBSD
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesnumerics, 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.noyesno
Secondary indexesyesyesno
SQL infoSupport of SQLnoyes infoSQL 2003 with some extensionsyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsRESTful HTTP APIJDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP API
Supported programming languagesC#
C++
F#
Visual Basic
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
any language that supports HTTP calls
Server-side scripts infoStored proceduresyesyes, in SQL, C, Ruser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
Triggersnoyesyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding via remote tablesyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoSource-replica replication available in experimental statusSource-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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
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.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
Graph Engine infoformer name: TrinityMonetDBTimescaleDBYanza
Recent citations in the news

Trinity
30 October 2010, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
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TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

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4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
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Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
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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