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DBMS > Databricks vs. Datomic vs. FileMaker vs. GridDB

System Properties Comparison Databricks vs. Datomic vs. FileMaker vs. GridDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDatomic  Xexclude from comparisonFileMaker  Xexclude from comparisonGridDB  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.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFileMaker is a cross-platform RDBMS that includes a GUI frontend.Scalable in-memory time series database optimized for IoT and Big Data
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score47.91
Rank#20  Overall
#14  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Websitewww.databricks.comwww.datomic.comwww.claris.com/­filemakergriddb.net
Technical documentationdocs.databricks.comdocs.datomic.comwww.claris.com/­resources/­documentationdocs.griddb.net
DeveloperDatabricksCognitectClaris infoa subsidiary of AppleToshiba Corporation
Initial release2013201219832013
Current release1.0.7075, December 202319.4.1, November 20215.1, August 2022
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++
Server operating systemshostedAll OS with a Java VMiOS infoclient part only
Linux
OS X
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestamp
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.yesnoyes infoA http query request can return the data in XML formatno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLwith Databricks SQLnoyes infovia pluginsSQL92, SQL-like TQL (Toshiba Query Language)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIFilemaker WebDirect
JDBC
ODBC
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
Clojure
Java
PHPC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoTransaction Functionsyesno
TriggersBy using transaction functionsyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesnone infoBut extensive use of caching in the application peersSource-replica replication, warm standby infosince Version 14Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobs
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containers
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID at container level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyes
User concepts infoAccess controlnosimple rights management via user accounts and connection to external directory servicesAccess rights for users can be defined per database
More information provided by the system vendor
DatabricksDatomicFileMakerGridDB
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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DatabricksDatomicFileMakerGridDB
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