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DBMS > GreptimeDB vs. Realm vs. Splice Machine vs. STSdb vs. Teradata Aster

System Properties Comparison GreptimeDB vs. Realm vs. Splice Machine vs. STSdb vs. Teradata Aster

Editorial information provided by DB-Engines
NameGreptimeDB  Xexclude from comparisonRealm  Xexclude from comparisonSplice Machine  Xexclude from comparisonSTSdb  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionAn open source Time Series DBMS built for increased scalability, high performance and efficiencyA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodPlatform for big data analytics on multistructured data sources and types
Primary database modelTime Series DBMSDocument storeRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.12
Rank#351  Overall
#34  Time Series DBMS
Score7.41
Rank#52  Overall
#8  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Websitegreptime.comrealm.iosplicemachine.comgithub.com/­STSSoft/­STSdb4
Technical documentationdocs.greptime.comrealm.io/­docssplicemachine.com/­how-it-works
DeveloperGreptime Inc.Realm, acquired by MongoDB in May 2019Splice MachineSTS Soft SCTeradata
Initial release20222014201420112005
Current release3.1, March 20214.0.8, September 2015
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoAGPL 3.0, commercial license availableOpen Source infoGPLv2, commercial license availablecommercial
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 languageRustJavaC#
Server operating systemsAndroid
Docker
FreeBSD
Linux
macOS
Windows
Android
Backend: server-less
iOS
Windows
Linux
OS X
Solaris
Windows
WindowsLinux
Data schemeschema-free, schema definition possibleyesyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyesyesyes infoprimitive types and user defined types (classes)yes
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 infoin Aster File Store
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLyesnoyesnoyes
APIs and other access methodsgRPC
HTTP API
JDBC
JDBC
Native Spark Datasource
ODBC
.NET Client APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC++
Erlang
Go
Java
JavaScript
.Net
Java infowith Android only
Objective-C
React Native
Swift
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C#
Java
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresPythonno inforuns within the applications so server-side scripts are unnecessaryyes infoJavanoR packages
Triggersyes infoChange Listenersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShared Nothhing Auto-Sharding, Columnar PartitioningnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
noneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.yes infoIn-Memory realmyesno
User concepts infoAccess controlSimple rights management via user accountsyesAccess rights for users, groups and roles according to SQL-standardnofine grained access rights according to SQL-standard
More information provided by the system vendor
GreptimeDBRealmSplice MachineSTSdbTeradata Aster
Specific characteristicsGreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more
Competitive advantages- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more
Typical application scenariosFor IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more
Key customersGreptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more
Market metricsGreptimeDB has garnered global recognition by topping GitHub trends following its...
» more
Licensing and pricing modelsGreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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More resources
GreptimeDBRealmSplice MachineSTSdbTeradata Aster
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