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DBMS > Databricks vs. GridDB vs. OrientDB vs. TimescaleDB vs. Tkrzw

System Properties Comparison Databricks vs. GridDB vs. OrientDB vs. TimescaleDB vs. Tkrzw

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridDB  Xexclude from comparisonOrientDB  Xexclude from comparisonTimescaleDB  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  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 DataMulti-model DBMS (Document, Graph, Key/Value)A 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 modelDocument store
Relational DBMS
Time Series DBMSDocument store
Graph DBMS
Key-value store
Time Series DBMSKey-value store
Secondary database modelsKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score3.02
Rank#88  Overall
#16  Document stores
#6  Graph DBMS
#12  Key-value stores
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Score0.00
Rank#385  Overall
#61  Key-value stores
Websitewww.databricks.comgriddb.netorientdb.orgwww.timescale.comdbmx.net/­tkrzw
Technical documentationdocs.databricks.comdocs.griddb.netwww.orientdb.com/­docs/­last/­index.htmldocs.timescale.com
DeveloperDatabricksToshiba CorporationOrientDB LTD; CallidusCloud; SAPTimescaleMikio Hirabayashi
Initial release20132013201020172020
Current release5.1, August 20223.2.29, March 20242.15.0, May 20240.9.3, August 2020
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaCC++
Server operating systemshostedLinuxAll OS with a Java JDK (>= JDK 6)Linux
OS X
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free infoSchema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")yesschema-free
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 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.yesnonoyesno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLSQL92, SQL-like TQL (Toshiba Query Language)SQL-like query language, no joinsyes infofull PostgreSQL SQL syntaxno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
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
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoJava, Javascriptuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellno
TriggersyesHooksyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, across time and space (hash partitioning) attributesnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replicationSource-replica replication with hot standby and reads on replicas infonone
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno infocould be achieved with distributed queriesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationship in graphsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesnoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users and roles; record level security configurablefine grained access rights according to SQL-standardno
More information provided by the system vendor
DatabricksGridDBOrientDBTimescaleDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksGridDBOrientDBTimescaleDBTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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