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DBMS > AllegroGraph vs. Elasticsearch vs. etcd vs. Microsoft Azure Data Explorer vs. Titan

System Properties Comparison AllegroGraph vs. Elasticsearch vs. etcd vs. Microsoft Azure Data Explorer vs. Titan

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonElasticsearch  Xexclude from comparisonetcd  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTitan  Xexclude from comparison
Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSA distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricA distributed reliable key-value storeFully managed big data interactive analytics platformTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Search engineKey-value storeRelational DBMS infocolumn orientedGraph DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
Vector DBMS
Document 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
Score1.06
Rank#187  Overall
#30  Document stores
#17  Graph DBMS
#7  RDF stores
#7  Vector DBMS
Score135.35
Rank#7  Overall
#1  Search engines
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websiteallegrograph.comwww.elastic.co/­elasticsearchetcd.io
github.com/­etcd-io/­etcd
azure.microsoft.com/­services/­data-explorergithub.com/­thinkaurelius/­titan
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­thinkaurelius/­titan/­wiki
DeveloperFranz Inc.ElasticMicrosoftAurelius, owned by DataStax
Initial release2004201020192012
Current release8.0, December 20238.6, January 20233.4, August 2019cloud service with continuous releases
License infoCommercial or Open Sourcecommercial infoLimited community edition freeOpen Source infoElastic LicenseOpen Source infoApache Version 2.0commercialOpen Source infoApache license, version 2.0
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 languageJavaGoJava
Server operating systemsLinux
OS X
Windows
All OS with a Java VMFreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Unix
Windows
Data schemeyes infoRDF schemasschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesnoyes 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 possiblenonoyes
Secondary indexesyesyes infoAll search fields are automatically indexednoall fields are automatically indexedyes
SQL infoSupport of SQLSPARQL is used as query languageSQL-like query languagenoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsRESTful HTTP API
SPARQL
Java API
RESTful HTTP/JSON API
gRPC
JSON over HTTP
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Clojure
Java
Python
Server-side scripts infoStored proceduresyes infoJavaScript or Common LispyesnoYes, possible languages: KQL, Python, Ryes
Triggersyesyes infoby using the 'percolation' featureyes, watching key changesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingSharding infoImplicit feature of the cloud serviceyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop ConnectornoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonononoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noMemcached and Redis integrationnono
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnoAzure Active Directory AuthenticationUser authentification and security via Rexster Graph Server
More information provided by the system vendor
AllegroGraphElasticsearchetcdMicrosoft Azure Data ExplorerTitan
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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