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DBMS > Databricks vs. Firebase Realtime Database vs. Riak KV vs. Sphinx

System Properties Comparison Databricks vs. Firebase Realtime Database vs. Riak KV vs. Sphinx

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonRiak KV  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.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Distributed, fault tolerant key-value storeOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Relational DBMS
Document storeKey-value store infowith links between data sets and object tags for the creation of secondary indexesSearch 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
Score14.29
Rank#39  Overall
#6  Document stores
Score4.10
Rank#82  Overall
#9  Key-value stores
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.databricks.comfirebase.google.com/­products/­realtime-databasesphinxsearch.com
Technical documentationdocs.databricks.comfirebase.google.com/­docs/­databasewww.tiot.jp/­riak-docs/­riak/­kv/­latestsphinxsearch.com/­docs
DeveloperDatabricksGoogle infoacquired by Google 2014OpenSource, formerly Basho TechnologiesSphinx Technologies Inc.
Initial release2013201220092001
Current release3.2.0, December 20223.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2, commercial enterprise editionOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangC++
Server operating systemshostedhostedLinux
OS X
FreeBSD
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.yesnono
Secondary indexesyesyesrestrictedyes infofull-text index on all search fields
SQL infoSupport of SQLwith Databricks SQLnonoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Android
iOS
JavaScript API
RESTful HTTP API
HTTP API
Native Erlang Interface
Proprietary protocol
Supported programming languagesPython
R
Scala
Java
JavaScript
Objective-C
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions and aggregateslimited functionality with using 'rules'Erlangno
TriggersCallbacks are triggered when data changesyes infopre-commit hooks and post-commit hooksno
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency
Foreign keys infoReferential integritynono infolinks between data sets can be storedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnono
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.no
User concepts infoAccess controlyes, based on authentication and database rulesyes, using Riak Securityno
More information provided by the system vendor
DatabricksFirebase Realtime DatabaseRiak KVSphinx
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksFirebase Realtime DatabaseRiak KVSphinx
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