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DBMS > Firebase Realtime Database vs. Fujitsu Enterprise Postgres vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer

System Properties Comparison Firebase Realtime Database vs. Fujitsu Enterprise Postgres vs. Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  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.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.A widely adopted in-memory data gridWell established RDBMSFully managed big data interactive analytics platform
Primary database modelDocument storeRelational DBMSKey-value storeRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument store
Spatial DBMS
Document store infoJSON support with IMDG 3.12Document store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.64
Rank#39  Overall
#6  Document stores
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasewww.postgresql.fastware.comhazelcast.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorer
Technical documentationfirebase.google.com/­docs/­databasewww.postgresql.fastware.com/­product-manualshazelcast.org/­imdg/­docsdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperGoogle infoacquired by Google 2014PostgreSQL Global Development Group, Fujitsu Australia Software TechnologyHazelcastActian CorporationMicrosoft
Initial release201220081974 infooriginally developed at University Berkely in early 1970s2019
Current releaseFujitsu Enterprise Postgres 14, January 20225.3.6, November 202311.2, May 2022cloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCJavaC
Server operating systemshostedLinux
Windows
All OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hosted
Data schemeschema-freeyesschema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or dateyesyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.noyes infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availableyes
Secondary indexesyesyesyesyesall fields are automatically indexed
SQL infoSupport of SQLnoyesSQL-like query languageyesKusto Query Language (KQL), SQL subset
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJava
JavaScript
Objective-C
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored procedureslimited functionality with using 'rules'user defined functionsyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, R
TriggersCallbacks are triggered when data changesyesyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodespartitioning by range, list and by hashShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes infoReplicated MapIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDone or two-phase-commit; repeatable reads; read commitedACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlyes, based on authentication and database rulesfine grained access rights according to SQL-standardRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
Firebase Realtime DatabaseFujitsu Enterprise PostgresHazelcastIngresMicrosoft Azure Data Explorer
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