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DBMS > AllegroGraph vs. GigaSpaces vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sqrrl

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

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonGigaSpaces  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSqrrl  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.
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA widely adopted in-memory data gridFully managed big data interactive analytics platformAdaptable, secure NoSQL built on Apache Accumulo
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document store
Object oriented DBMS infoValues are user defined objects
Key-value storeRelational DBMS infocolumn orientedDocument store
Graph DBMS
Key-value store
Wide column store
Secondary database modelsSpatial DBMSGraph DBMS
Search engine
Document 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
Score1.13
Rank#179  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#9  Vector DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Websiteallegrograph.comwww.gigaspaces.comhazelcast.comazure.microsoft.com/­services/­data-explorersqrrl.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.gigaspaces.com/­latest/­landing.htmlhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperFranz Inc.Gigaspaces TechnologiesHazelcastMicrosoftAmazon infooriginally Sqrrl Data, Inc.
Initial release20042000200820192012
Current release8.0, December 202315.5, September 20205.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetJavaJava
Server operating systemsLinux
OS X
Windows
Linux
macOS
Solaris
Windows
All OS with a Java VMhostedLinux
Data schemeyes infoRDF schemasschema-freeschema-freeFixed 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-typesyes
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 possibleno infoXML can be used for describing objects metadatayes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-99 for query and DML statementsSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP API
SPARQL
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
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
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
C++
Java
Python
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
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispyesyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rno
Triggersyesyes, event driven architectureyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingShardingSharding infoImplicit feature of the cloud serviceSharding infomaking use of Hadoop
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.selectable replication factor infomaking use of Hadoop
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate 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.
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDone or two-phase-commit; repeatable reads; read commitednoAtomic updates per row, document, or graph entity
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.noyesyesno
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationRole-based access controlRole-based access controlAzure Active Directory AuthenticationCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)
More information provided by the system vendor
AllegroGraphGigaSpacesHazelcastMicrosoft Azure Data ExplorerSqrrl
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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