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DBMS > AllegroGraph vs. Databricks vs. Elasticsearch vs. Sphinx vs. Yaacomo

System Properties Comparison AllegroGraph vs. Databricks vs. Elasticsearch vs. Sphinx vs. Yaacomo

Editorial information provided by DB-Engines
NameAllegroGraph  Xexclude from comparisonDatabricks  Xexclude from comparisonElasticsearch  Xexclude from comparisonSphinx  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionHigh performance, persistent RDF store with additional support for Graph DBMSThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.A 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 metricOpen source search engine for searching in data from different sources, e.g. relational databasesOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store infowith version 6.5
Graph DBMS
RDF store
Vector DBMS
Document store
Relational DBMS
Search engineSearch engineRelational DBMS
Secondary database modelsSpatial DBMSDocument store
Spatial DBMS
Vector 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
#8  Vector DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score132.83
Rank#7  Overall
#1  Search engines
Score5.95
Rank#55  Overall
#5  Search engines
Websiteallegrograph.comwww.databricks.comwww.elastic.co/­elasticsearchsphinxsearch.comyaacomo.com
Technical documentationfranz.com/­agraph/­support/­documentation/­current/­agraph-introduction.htmldocs.databricks.comwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlsphinxsearch.com/­docs
DeveloperFranz Inc.DatabricksElasticSphinx Technologies Inc.Q2WEB GmbH
Initial release20042013201020012009
Current release8.0, December 20238.6, January 20233.5.1, February 2023
License infoCommercial or Open Sourcecommercial infoLimited community edition freecommercialOpen Source infoElastic LicenseOpen Source infoGPL version 2, commercial licence availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemsLinux
OS X
Windows
hostedAll OS with a Java VMFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeyes infoRDF schemasFlexible Schema (defined schema, partial schema, schema free)schema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
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 possibleyesnono
Secondary indexesyesyesyes infoAll search fields are automatically indexedyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSPARQL is used as query languagewith Databricks SQLSQL-like query languageSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP API
SPARQL
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Proprietary protocolJDBC
ODBC
Supported programming languagesC#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala
Python
R
Scala
.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infoJavaScript or Common Lispuser defined functions and aggregatesyesno
Triggersyesyes infoby using the 'percolation' featurenoyes
Partitioning methods infoMethods for storing different data on different nodeswith FederationShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yesyesnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoES-Hadoop Connectornono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate Consistency
Foreign keys infoReferential integritynononoyes
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 persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoMemcached and Redis integrationyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user roles and pluggable authenticationnofine grained access rights according to SQL-standard
More information provided by the system vendor
AllegroGraphDatabricksElasticsearchSphinxYaacomo
Specific characteristicsKnowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more
Supported database models : In addition to the Document store and Relational DBMS...
» more
Competitive advantagesAllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more
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