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DBMS > Databricks vs. GridDB vs. Realm vs. TimescaleDB

System Properties Comparison Databricks vs. GridDB vs. Realm vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridDB  Xexclude from comparisonRealm  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Scalable in-memory time series database optimized for IoT and Big DataA DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Relational DBMS
Time Series DBMSDocument storeTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score7.60
Rank#52  Overall
#9  Document stores
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.databricks.comgriddb.netrealm.iowww.timescale.com
Technical documentationdocs.databricks.comdocs.griddb.netrealm.io/­docsdocs.timescale.com
DeveloperDatabricksToshiba CorporationRealm, acquired by MongoDB in May 2019Timescale
Initial release2013201320142017
Current release5.1, August 20222.13.0, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C
Server operating systemshostedLinuxAndroid
Backend: server-less
iOS
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesnumerics, 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.yesnonoyes
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL92, SQL-like TQL (Toshiba Query Language)noyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Java infowith Android only
Objective-C
React Native
Swift
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnono inforuns within the applications so server-side scripts are unnecessaryuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes infoChange Listenersyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnoneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoIn-Memory realmno
User concepts infoAccess controlAccess rights for users can be defined per databaseyesfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksGridDBRealmTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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DatabricksGridDBRealmTimescaleDB
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