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DBMS > Firebase Realtime Database vs. Google Cloud Spanner vs. Hawkular Metrics vs. Sphinx vs. Splice Machine

System Properties Comparison Firebase Realtime Database vs. Google Cloud Spanner vs. Hawkular Metrics vs. Sphinx vs. Splice Machine

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Open source search engine for searching in data from different sources, e.g. relational databasesOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument storeRelational DBMSTime Series DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.64
Rank#39  Overall
#6  Document stores
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasecloud.google.com/­spannerwww.hawkular.orgsphinxsearch.comsplicemachine.com
Technical documentationfirebase.google.com/­docs/­databasecloud.google.com/­spanner/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidesphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperGoogle infoacquired by Google 2014GoogleCommunity supported by Red HatSphinx Technologies Inc.Splice Machine
Initial release20122017201420012014
Current release3.5.1, February 20233.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemshostedhostedLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesnoyes
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.nonono
Secondary indexesyesyesnoyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infoQuery statements complying to ANSI 2011noSQL-like query language (SphinxQL)yes
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
HTTP RESTProprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languagesJava
JavaScript
Objective-C
Go
Java
JavaScript (Node.js)
Python
Go
Java
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored procedureslimited functionality with using 'rules'nononoyes infoJava
TriggersCallbacks are triggered when data changesnoyes infovia Hawkular Alertingnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication with 3 replicas for regional instances.selectable replication factor infobased on CassandranoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflownonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID infoStrict serializable isolationnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nonoAccess rights for users, groups and roles according to SQL-standard

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More resources
Firebase Realtime DatabaseGoogle Cloud SpannerHawkular MetricsSphinxSplice Machine
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