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DBMS > Firebase Realtime Database vs. JanusGraph vs. Machbase Neo vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB

System Properties Comparison Firebase Realtime Database vs. JanusGraph vs. Machbase Neo vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonJanusGraph infosuccessor of Titan  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Berkeley DB  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 Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017TimeSeries DBMS for AIoT and BigDataFully managed big data interactive analytics platformWidely used in-process key-value store
Primary database modelDocument storeGraph DBMSTime Series DBMSRelational DBMS infocolumn orientedKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsDocument 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
Score2.02
Rank#125  Overall
#12  Graph DBMS
Score0.17
Rank#337  Overall
#30  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Websitefirebase.google.com/­products/­realtime-databasejanusgraph.orgmachbase.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationfirebase.google.com/­docs/­databasedocs.janusgraph.orgmachbase.com/­dbmsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperGoogle infoacquired by Google 2014Linux Foundation; originally developed as Titan by AureliusMachbaseMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20122017201320191994
Current release0.6.3, February 2023V8.0, August 2023cloud service with continuous releases18.1.40, May 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree test version availablecommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemshostedLinux
OS X
Unix
Windows
Linux
macOS
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeyesyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.nononoyesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLnonoSQL-like query languageKusto Query Language (KQL), SQL subsetyes infoSQL interfaced based on SQLite is available
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJava
JavaScript
Objective-C
Clojure
Java
Python
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Server-side scripts infoStored procedureslimited functionality with using 'rules'yesnoYes, possible languages: KQL, Python, Rno
TriggersCallbacks are triggered when data changesyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)ShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Faunus, a graph analytics enginenoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infovolatile and lookup tablenoyes
User concepts infoAccess controlyes, based on authentication and database rulesUser authentification and security via Rexster Graph Serversimple password-based access controlAzure Active Directory Authenticationno

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More resources
Firebase Realtime DatabaseJanusGraph infosuccessor of TitanMachbase Neo infoFormer name was InfinifluxMicrosoft Azure Data ExplorerOracle Berkeley DB
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