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DBMS > Databricks vs. Realm vs. Sphinx

System Properties Comparison Databricks vs. Realm vs. Sphinx

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonRealm  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 DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core DataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Document storeSearch 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
Score7.60
Rank#52  Overall
#9  Document stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comrealm.iosphinxsearch.com
Technical documentationdocs.databricks.comrealm.io/­docssphinxsearch.com/­docs
DeveloperDatabricksRealm, acquired by MongoDB in May 2019Sphinx Technologies Inc.
Initial release201320142001
Current release3.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedAndroid
Backend: server-less
iOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesno
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
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Proprietary protocol
Supported programming languagesPython
R
Scala
.Net
Java infowith Android only
Objective-C
React Native
Swift
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregatesno inforuns within the applications so server-side scripts are unnecessaryno
Triggersyes infoChange Listenersno
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyesyes 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.noyes infoIn-Memory realm
User concepts infoAccess controlyesno
More information provided by the system vendor
DatabricksRealmSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksRealmSphinx
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