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DBMS > AlaSQL vs. AllegroGraph vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB

System Properties Comparison AlaSQL vs. AllegroGraph vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. Oracle Berkeley DB

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonAllegroGraph  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparison
DescriptionJavaScript DBMS libraryHigh performance, persistent RDF store with additional support for Graph DBMSCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Fully managed big data interactive analytics platformWidely used in-process key-value store
Primary database modelDocument store
Relational DBMS
Document store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document storeRelational DBMS infocolumn orientedKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Secondary database modelsSpatial DBMSDocument 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
Score0.46
Rank#260  Overall
#40  Document stores
#121  Relational DBMS
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Websitealasql.orgallegrograph.comfirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­services/­data-explorerwww.oracle.com/­database/­technologies/­related/­berkeleydb.html
Technical documentationgithub.com/­AlaSQL/­alasqlfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlfirebase.google.com/­docs/­databasedocs.microsoft.com/­en-us/­azure/­data-explorerdocs.oracle.com/­cd/­E17076_05/­html/­index.html
DeveloperAndrey Gershun & Mathias R. WulffFranz Inc.Google infoacquired by Google 2014MicrosoftOracle infooriginally developed by Sleepycat, which was acquired by Oracle
Initial release20142004201220191994
Current release8.0, December 2023cloud service with continuous releases18.1.40, May 2020
License infoCommercial or Open SourceOpen Source infoMIT-Licensecommercial infoLimited community edition freecommercialcommercialOpen Source infocommercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptC, Java, C++ (depending on the Berkeley DB edition)
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)Linux
OS X
Windows
hostedhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Data schemeschema-freeyes infoRDF schemasschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or datenoyesyesyes 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.nono infobulk load of XML files possiblenoyesyes infoonly with the Berkeley DB XML edition
Secondary indexesnoyesyesall fields are automatically indexedyes
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.SPARQL is used as query languagenoKusto Query Language (KQL), SQL subsetyes infoSQL interfaced based on SQLite is available
APIs and other access methodsJavaScript APIRESTful HTTP API
SPARQL
Android
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJavaScriptC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Java
JavaScript
Objective-C
.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 proceduresnoyes infoJavaScript or Common Lisplimited functionality with using 'rules'Yes, possible languages: KQL, Python, Rno
TriggersyesyesCallbacks are triggered when data changesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoonly for the SQL API
Partitioning methods infoMethods for storing different data on different nodesnonewith FederationSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
yes 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 methodsnononoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storageACIDyesnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlnoUsers with fine-grained authorization concept, user roles and pluggable authenticationyes, based on authentication and database rulesAzure Active Directory Authenticationno
More information provided by the system vendor
AlaSQLAllegroGraphFirebase Realtime DatabaseMicrosoft Azure Data ExplorerOracle Berkeley DB
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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