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DBMS > Databricks vs. Elasticsearch vs. GridGain vs. Sphinx

System Properties Comparison Databricks vs. Elasticsearch vs. GridGain vs. Sphinx

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonElasticsearch  Xexclude from comparisonGridGain  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.A distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricGridGain is an in-memory computing platform, built on Apache IgniteOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Search engineKey-value store
Relational DBMS
Search engine
Secondary database modelsDocument store
Spatial DBMS
Vector 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
Score135.35
Rank#7  Overall
#1  Search engines
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comwww.elastic.co/­elasticsearchwww.gridgain.comsphinxsearch.com
Technical documentationdocs.databricks.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlwww.gridgain.com/­docs/­index.htmlsphinxsearch.com/­docs
DeveloperDatabricksElasticGridGain Systems, Inc.Sphinx Technologies Inc.
Initial release2013201020072001
Current release8.6, January 2023GridGain 8.5.13.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoElastic LicensecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
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.yesnoyes
Secondary indexesyesyes infoAll search fields are automatically indexedyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLSQL-like query languageANSI-99 for query and DML statements, subset of DDLSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol
Supported programming languagesPython
R
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyes (compute grid and cache interceptors can be used instead)no
Triggersyes infoby using the 'percolation' featureyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsES-Hadoop Connectoryes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.noMemcached and Redis integrationyes
User concepts infoAccess controlSecurity Hooks for custom implementationsno
More information provided by the system vendor
DatabricksElasticsearchGridGainSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksElasticsearchGridGainSphinx
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