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DBMS > Databricks vs. DataFS vs. GridGain vs. MarkLogic vs. Sphinx

System Properties Comparison Databricks vs. DataFS vs. GridGain vs. MarkLogic vs. Sphinx

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonDataFS  Xexclude from comparisonGridGain  Xexclude from comparisonMarkLogic  Xexclude from comparisonSphinx  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 IgniteOperational and transactional Enterprise NoSQL databaseOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Object oriented DBMSKey-value store
Relational DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engine
Secondary database modelsGraph 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
Score0.06
Rank#354  Overall
#15  Object oriented DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comnewdatabase.comwww.gridgain.comwww.marklogic.comsphinxsearch.com
Technical documentationdocs.databricks.comdev.mobiland.com/­Overview.xspwww.gridgain.com/­docs/­index.htmldocs.marklogic.comsphinxsearch.com/­docs
DeveloperDatabricksMobiland AGGridGain Systems, Inc.MarkLogic Corp.Sphinx Technologies Inc.
Initial release20132018200720012001
Current release1.1.263, October 2022GridGain 8.5.111.0, December 20223.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence available
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
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
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)yesschema-free infoSchema can be enforcedyes
Typing infopredefined data types such as float or dateyesyesyesno
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.yesnoyesyes
Secondary indexesyesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLnoANSI-99 for query and DML statements, subset of DDLyes infoSQL92SQL-like query language (SphinxQL)
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
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
Proprietary protocol
Supported programming languagesPython
R
Scala
.Net
C
C#
C++
VB.Net
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)yes infovia XQuery or JavaScriptno
Triggersno, except callback-events from server when changes happenedyes (cache interceptors and events)yesno
Partitioning methods infoMethods for storing different data on different nodesProprietary Sharding systemShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)yes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infocan act as a resource manager in an XA/JTA transactionno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes, with Range Indexes
User concepts infoAccess controlWindows-ProfileSecurity Hooks for custom implementationsRole-based access control at the document and subdocument levelsno
More information provided by the system vendor
DatabricksDataFSGridGainMarkLogicSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksDataFSGridGainMarkLogicSphinx
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