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DBMS > AnzoGraph DB vs. Apache Impala vs. Elasticsearch vs. OrigoDB vs. Spark SQL

System Properties Comparison AnzoGraph DB vs. Apache Impala vs. Elasticsearch vs. OrigoDB vs. Spark SQL

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache Impala  Xexclude from comparisonElasticsearch  Xexclude from comparisonOrigoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationAnalytic DBMS for HadoopA 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 fully ACID in-memory object graph databaseSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelGraph DBMS
RDF store
Relational DBMSSearch engineDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score14.03
Rank#40  Overall
#24  Relational DBMS
Score134.78
Rank#7  Overall
#1  Search engines
Score0.03
Rank#378  Overall
#51  Document stores
#18  Object oriented DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websitecambridgesemantics.com/­anzographimpala.apache.orgwww.elastic.co/­elasticsearchorigodb.comspark.apache.org/­sql
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmimpala.apache.org/­impala-docs.htmlwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlorigodb.com/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCambridge SemanticsApache Software Foundation infoApache top-level project, originally developed by ClouderaElasticRobert Friberg et alApache Software Foundation
Initial release2018201320102009 infounder the name LiveDB2014
Current release2.3, January 20214.1.0, June 20228.6, January 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2Open Source infoElastic LicenseOpen SourceOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC#Scala
Server operating systemsLinuxLinuxAll OS with a Java VMLinux
Windows
Linux
OS X
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesschema-free infoFlexible type definitions. Once a type is defined, it is persistentyesyes
Typing infopredefined data types such as float or dateyesyesUser defined using .NET types and collectionsyes
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.nononono infocan be achieved using .NETno
Secondary indexesnoyesyes infoAll search fields are automatically indexedyesno
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.SQL-like DML and DDL statementsSQL-like query languagenoSQL-like DML and DDL statements
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
Java API
RESTful HTTP/JSON API
.NET Client API
HTTP API
LINQ
JDBC
ODBC
Supported programming languagesC++
Java
Python
All languages supporting JDBC/ODBC.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
.NetJava
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infouser defined functions and integration of map-reduceyesyesno
Triggersnonoyes infoby using the 'percolation' featureyes infoDomain Eventsno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardinghorizontal partitioning infoclient side managed; servers are not synchronizedyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusterselectable replication factoryesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes infoquery execution via MapReduceES-Hadoop Connectorno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterEventual ConsistencyEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all
Foreign keys infoReferential integrityno infonot needed in graphsnonodepending on modelno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoMemcached and Redis integrationyesno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users, groups and roles infobased on Apache Sentry and KerberosRole based authorizationno

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More resources
AnzoGraph DBApache ImpalaElasticsearchOrigoDBSpark SQL
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