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DBMS > Databricks vs. GigaSpaces vs. IBM Cloudant vs. Sphinx

System Properties Comparison Databricks vs. GigaSpaces vs. IBM Cloudant vs. Sphinx

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGigaSpaces  Xexclude from comparisonIBM Cloudant  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.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsDatabase as a Service offering based on Apache CouchDBOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Document storeSearch engine
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score2.68
Rank#106  Overall
#20  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comwww.gigaspaces.comwww.ibm.com/­products/­cloudantsphinxsearch.com
Technical documentationdocs.databricks.comdocs.gigaspaces.com/­latest/­landing.htmlcloud.ibm.com/­docs/­Cloudantsphinxsearch.com/­docs
DeveloperDatabricksGigaspaces TechnologiesIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Sphinx Technologies Inc.
Initial release2013200020102001
Current release15.5, September 20203.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetErlangC++
Server operating systemshostedLinux
macOS
Solaris
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnono
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.yesno infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLSQL-99 for query and DML statementsnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
RESTful HTTP/JSON APIProprietary protocol
Supported programming languagesPython
R
Scala
.Net
C++
Java
Python
Scala
C#
Java
JavaScript
Objective-C
PHP
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesView functions (Map-Reduce) in JavaScriptno
Triggersyes, event driven architectureyesno
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 nodesyesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Multi-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno infoatomic operations within a document possibleno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic lockingyes
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.noyesno
User concepts infoAccess controlRole-based access controlAccess rights for users can be defined per databaseno
More information provided by the system vendor
DatabricksGigaSpacesIBM CloudantSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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