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

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

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonVoltDB  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.TimeSeries DBMS for AIoT and BigDataFully managed big data interactive analytics platformWidely used in-process key-value storeDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelDocument storeTime Series DBMSRelational DBMS infocolumn orientedKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMS
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
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
Score1.47
Rank#157  Overall
#73  Relational DBMS
Websitefirebase.google.com/­products/­realtime-databasemachbase.comazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlwww.voltdb.com
Technical documentationfirebase.google.com/­docs/­databasemachbase.com/­dbmsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­cd/­E17076_05/­html/­index.htmldocs.voltdb.com
DeveloperGoogle infoacquired by Google 2014MachbaseMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleVoltDB Inc.
Initial release20122013201919942010
Current releaseV8.0, August 2023cloud service with continuous releases18.1.40, May 202011.3, April 2022
License infoCommercial or Open Sourcecommercialcommercial infofree test version availablecommercialOpen Source infocommercial license availableOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC, Java, C++ (depending on the Berkeley DB edition)Java, C++
Server operating systemshostedLinux
macOS
Windows
hostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X infofor development
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesnoyes
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.nonoyesyes infoonly with the Berkeley DB XML edition
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like query languageKusto Query Language (KQL), SQL subsetyes infoSQL interfaced based on SQLite is availableyes infoonly a subset of SQL 99
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesJava
JavaScript
Objective-C
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
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored procedureslimited functionality with using 'rules'noYes, possible languages: KQL, Python, RnoJava
TriggersCallbacks are triggered when data changesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
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
Foreign keys infoReferential integritynonononono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACIDACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesnoyesyesyes infoSnapshots and command logging
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 rulessimple password-based access controlAzure Active Directory AuthenticationnoUsers and roles with access to stored procedures

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More resources
Firebase Realtime DatabaseMachbase Neo infoFormer name was InfinifluxMicrosoft Azure Data ExplorerOracle Berkeley DBVoltDB
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