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DBMS > Databricks vs. DataFS vs. GridGain vs. Sphinx vs. SWC-DB

System Properties Comparison Databricks vs. DataFS vs. GridGain vs. Sphinx vs. SWC-DB

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDataFS  Xexclude from comparisonGridGain  Xexclude from comparisonSphinx  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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.All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.GridGain is an in-memory computing platform, built on Apache IgniteOpen source search engine for searching in data from different sources, e.g. relational databasesA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Relational DBMS
Object oriented DBMSKey-value store
Relational DBMS
Search engineWide column store
Secondary database modelsGraph DBMSTime Series 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
Score0.09
Rank#360  Overall
#17  Object oriented DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.08
Rank#364  Overall
#13  Wide column stores
Websitewww.databricks.comnewdatabase.comwww.gridgain.comsphinxsearch.comgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.databricks.comdev.mobiland.com/­Overview.xspwww.gridgain.com/­docs/­index.htmlsphinxsearch.com/­docs
DeveloperDatabricksMobiland AGGridGain Systems, Inc.Sphinx Technologies Inc.Alex Kashirin
Initial release20132018200720012020
Current release1.1.263, October 2022GridGain 8.5.13.5.1, February 20230.5, April 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoGPL V3
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetC++C++
Server operating systemshostedWindowsLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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.yesnoyesno
Secondary indexesyesnoyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLnoANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)SQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
Proprietary client DLL
WinRT client
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocolProprietary protocol
Thrift
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
VB.Net
C#
C++
Java
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)nono
Triggersno, except callback-events from server when changes happenedyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlWindows-ProfileSecurity Hooks for custom implementationsno
More information provided by the system vendor
DatabricksDataFSGridGainSphinxSWC-DB infoSuper Wide Column Database
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDataFSGridGainSphinxSWC-DB infoSuper Wide Column Database
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