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DBMS > Graph Engine vs. Teradata Aster vs. TimescaleDB vs. Tkrzw

System Properties Comparison Graph Engine vs. Teradata Aster vs. TimescaleDB vs. Tkrzw

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation enginePlatform for big data analytics on multistructured data sources and typesA 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
Relational 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.timescale.comdbmx.net/­tkrzw
Technical documentationwww.graphengine.io/­docs/­manualdocs.timescale.com
DeveloperMicrosoftTeradataTimescaleMikio Hirabayashi
Initial release2010200520172020
Current release2.15.0, 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 CCC++
Server operating systems.NETLinuxLinux
OS X
Windows
Linux
macOS
Data schemeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeyesschema-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.noyes infoin Aster File Storeyesno
Secondary indexesyesyes
SQL infoSupport of SQLnoyesyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
F#
Visual Basic
C
C#
C++
Java
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyesR packagesuser 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 partitioningShardingyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.Source-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoSQL Map-Reduce Frameworknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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 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: TrinityTeradata AsterTimescaleDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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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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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