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

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

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridGain  Xexclude from comparisonMarkLogic  Xexclude from comparisonSphinx  Xexclude from comparisonVoltDB  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 databaseOpen source search engine for searching in data from different sources, e.g. relational databasesDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Document store
Native XML DBMS
RDF store infoas of version 7
Search engine
Search engineRelational 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
Score5.95
Rank#55  Overall
#5  Search engines
Score1.47
Rank#157  Overall
#73  Relational DBMS
Websitewww.databricks.comwww.gridgain.comwww.marklogic.comsphinxsearch.comwww.voltdb.com
Technical documentationdocs.databricks.comwww.gridgain.com/­docs/­index.htmldocs.marklogic.comsphinxsearch.com/­docsdocs.voltdb.com
DeveloperDatabricksGridGain Systems, Inc.MarkLogic Corp.Sphinx Technologies Inc.VoltDB Inc.
Initial release20132007200120012010
Current releaseGridGain 8.5.111.0, December 20223.5.1, February 202311.3, April 2022
License infoCommercial or Open Sourcecommercialcommercialcommercial inforestricted free version is availableOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
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++Java, C++
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X infofor development
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free infoSchema can be enforcedyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.yesyesyes
Secondary indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLwith Databricks SQLANSI-99 for query and DML statements, subset of DDLyes infoSQL92SQL-like query language (SphinxQL)yes infoonly a subset of SQL 99
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
Proprietary protocolJava API
JDBC
RESTful HTTP/JSON API
Supported programming languagesPython
R
Scala
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
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)yes infovia XQuery or JavaScriptnoJava
Triggersyes (cache interceptors and events)yesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)yesnoneMulti-source replication
Source-replica replication
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 jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID infocan act as a resource manager in an XA/JTA transactionnoACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes infoSnapshots and command logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes, with Range Indexes
User concepts infoAccess controlSecurity Hooks for custom implementationsRole-based access control at the document and subdocument levelsnoUsers and roles with access to stored procedures
More information provided by the system vendor
DatabricksGridGainMarkLogicSphinxVoltDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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