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DBMS > AllegroGraph vs. Datomic vs. Microsoft Azure Data Explorer vs. STSdb vs. Vertica

System Properties Comparison AllegroGraph vs. Datomic vs. Microsoft Azure Data Explorer vs. STSdb vs. Vertica

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonDatomic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSTSdb  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityFully managed big data interactive analytics platformKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Relational DBMSRelational DBMS infocolumn orientedKey-value storeRelational DBMS infoColumn oriented
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
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websiteallegrograph.comwww.datomic.comazure.microsoft.com/­services/­data-explorergithub.com/­STSSoft/­STSdb4www.vertica.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.datomic.comdocs.microsoft.com/­en-us/­azure/­data-explorervertica.com/­documentation
DeveloperFranz Inc.CognitectMicrosoftSTS Soft SCOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20042012201920112005
Current release8.0, December 20231.0.6735, June 2023cloud service with continuous releases4.0.8, September 201512.0.3, January 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercial infolimited edition freecommercialOpen Source infoGPLv2, commercial license availablecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenonoyesnono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC#C++
Server operating systemsLinux
OS X
Windows
All OS with a Java VMhostedWindowsLinux
Data schemeyes infoRDF schemasyesFixed schema with schema-less datatypes (dynamic)yesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
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-typesyes infoprimitive types and user defined types (classes)yes
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.no infobulk load of XML files possiblenoyesno
Secondary indexesyesyesall fields are automatically indexednoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSPARQL is used as query languagenoKusto Query Language (KQL), SQL subsetnoFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsRESTful HTTP API
SPARQL
RESTful HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Clojure
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyes infoTransaction FunctionsYes, possible languages: KQL, Python, Rnoyes, PostgreSQL PL/pgSQL, with minor differences
TriggersyesBy using transaction functionsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeswith Federationnone infoBut extensive use of caching in the application peersSharding infoImplicit feature of the cloud servicenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
none infoBut extensive use of caching in the application peersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnoAzure Active Directory Authenticationnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
AllegroGraphDatomicMicrosoft Azure Data ExplorerSTSdbVertica infoOpenText™ Vertica™
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
» more
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