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

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

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonMarkLogic  Xexclude from comparisonSingleStore infoformer name was MemSQL  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.GridGain is an in-memory computing platform, built on Apache IgniteOperational and transactional Enterprise NoSQL databaseMySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table typeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSSearch engine
Secondary database modelsDocument store
Spatial DBMS
Time Series DBMS
Vector 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
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score5.18
Rank#63  Overall
#11  Document stores
#1  Native XML DBMS
#1  RDF stores
#7  Search engines
Score5.38
Rank#62  Overall
#35  Relational DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.databricks.comwww.gridgain.comwww.marklogic.comwww.singlestore.comsphinxsearch.com
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmldocs.marklogic.comdocs.singlestore.comsphinxsearch.com/­docs
DeveloperDatabricksGridGain Systems, Inc.MarkLogic Corp.SingleStore Inc.Sphinx Technologies Inc.
Initial release20132007200120132001
Current releaseGridGain 8.5.111.0, December 20228.5, January 20243.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availablecommercial infofree developer edition 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

Providers of DBaaS offerings, please contact us to be listed.
SingleStoreDB Cloud: The world's fastest, modern cloud database for both operational (OLTP) and analytical (OLAP) workloads. Available instantly with multi-cloud and hybrid-cloud capabilities
Implementation languageJava, C++, .NetC++C++, GoC++
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Linux info64 bit version requiredFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free infoSchema can be enforcedyesyes
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.yesyesyesno
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLyes infoSQL92yes infobut no triggers and foreign keysSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
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
Cluster Management API infoas HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC
Proprietary protocol
Supported programming languagesPython
R
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Bash
C
C#
Java
JavaScript (Node.js)
Python
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 JavaScriptyesno
Triggersyes (cache interceptors and events)yesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infohash partitioningSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)yesSource-replica replication infostores two copies of each physical data partition on two separate nodesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)yes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno infocan define user-defined aggregate functions for map-reduce-style calculationsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infocan act as a resource manager in an XA/JTA transactionACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes infoAll updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.yes 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.noyesyes, with Range Indexesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsRole-based access control at the document and subdocument levelsFine grained access control via users, groups and rolesno
More information provided by the system vendor
DatabricksGridGainMarkLogicSingleStore infoformer name was MemSQLSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
SingleStore offers a fully-managed , distributed, highly-scalable SQL database designed...
» more
Competitive advantagesSingleStore’s competitive advantages include: Easy and Simplified Architecture with...
» more
Typical application scenariosDriving Fast Analytics: SingleStore delivers the fastest and most scalable reporting...
» more
Key customersIEX Cloud : Improves Financial Data Distribution Speed 15x with Singlestore DB Comcast,...
» more
Market metricsCustomers in various industries worldwide including US and International Industry...
» more
Licensing and pricing modelsF ree Tier and Enterprise Edition
» more

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More resources
DatabricksGridGainMarkLogicSingleStore infoformer name was MemSQLSphinx
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