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DBMS > Graph Engine vs. Newts vs. Splice Machine vs. TimescaleDB

System Properties Comparison Graph Engine vs. Newts vs. Splice Machine vs. TimescaleDB

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Editorial information provided by DB-Engines
NameGraph Engine infoformer name: Trinity  Xexclude from comparisonNewts  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionA distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineTime Series DBMS based on CassandraOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelGraph DBMS
Key-value store
Time Series DBMSRelational DBMSTime Series DBMS
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
Score0.07
Rank#375  Overall
#41  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.graphengine.ioopennms.github.io/­newtssplicemachine.comwww.timescale.com
Technical documentationwww.graphengine.io/­docs/­manualgithub.com/­OpenNMS/­newts/­wikisplicemachine.com/­how-it-worksdocs.timescale.com
DeveloperMicrosoftOpenNMS GroupSplice MachineTimescale
Initial release2010201420142017
Current release3.1, March 20212.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoMIT LicenseOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache 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 CJavaJavaC
Server operating systems.NETLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesnoyesyes
SQL infoSupport of SQLnonoyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsRESTful HTTP APIHTTP REST
Java API
JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
F#
Visual Basic
JavaC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnoyes infoJavauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infobased on CassandraShared Nothhing Auto-Sharding, Columnar Partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
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.yesnoyesno
User concepts infoAccess controlnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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

Trinity
30 October 2010, Microsoft

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