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DBMS > AllegroGraph vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Teradata Aster

System Properties Comparison AllegroGraph vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sqrrl vs. Teradata Aster

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSA widely adopted in-memory data gridFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache AccumuloPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Key-value storeRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsSpatial DBMSDocument 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
Score0.84
Rank#204  Overall
#35  Document stores
#18  Graph DBMS
#7  RDF stores
#10  Vector DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score3.28
Rank#83  Overall
#45  Relational DBMS
Websiteallegrograph.comhazelcast.comazure.microsoft.com/­services/­data-explorersqrrl.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperFranz Inc.HazelcastMicrosoftAmazon infooriginally Sqrrl Data, Inc.Teradata
Initial release20042008201920122005
Current release8.0, December 20235.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsLinux
OS X
Windows
All OS with a Java VMhostedLinuxLinux
Data schemeyes infoRDF schemasschema-freeFixed schema with schema-less datatypes (dynamic)schema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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-typesyesyes
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 possibleyes infothe object must implement a serialization strategyyesyes infoin Aster File Store
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query languageKusto Query Language (KQL), SQL subsetnoyes
APIs and other access methodsRESTful HTTP API
SPARQL
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, RnoR packages
Triggersyesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynono
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingSharding infoImplicit feature of the cloud serviceSharding infomaking use of HadoopSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of Hadoopyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednoAtomic updates per row, document, or graph entityACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.noyesnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationRole-based access controlAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)fine grained access rights according to SQL-standard
More information provided by the system vendor
AllegroGraphHazelcastMicrosoft Azure Data ExplorerSqrrlTeradata Aster
News

AllegroGraph Named a 2024 Trend Setting Product
16 September 2024

Gartner recognized Franz Inc. as a Key Neuro-Symbolic AI Provider in 2024 Hype Cycle for AI
10 September 2024

Next-Generation Cybersecurity: Integrating Knowledge Graphs and Neuro-Symbolic AI with STIX and TAXII
10 September 2024

Pruning Cycles in UMLS Metathesaurus: A Neuro Symbolic AI Approach
9 September 2024

Awesome AI Companies – Franz Inc.
17 July 2024

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More resources
AllegroGraphHazelcastMicrosoft Azure Data ExplorerSqrrlTeradata Aster
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