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DBMS > AnzoGraph DB vs. GridGain vs. Solr vs. WakandaDB

System Properties Comparison AnzoGraph DB vs. GridGain vs. Solr vs. WakandaDB

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Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonGridGain  Xexclude from comparisonSolr  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationGridGain is an in-memory computing platform, built on Apache IgniteA widely used distributed, scalable search engine based on Apache LuceneWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelGraph DBMS
RDF store
Key-value store
Relational DBMS
Search engineObject oriented DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitecambridgesemantics.com/­anzographwww.gridgain.comsolr.apache.orgwakanda.github.io
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmwww.gridgain.com/­docs/­index.htmlsolr.apache.org/­resources.htmlwakanda.github.io/­doc
DeveloperCambridge SemanticsGridGain Systems, Inc.Apache Software FoundationWakanda SAS
Initial release2018200720062012
Current release2.3, January 2021GridGain 8.5.19.6.1, May 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercial infofree trial version availablecommercialOpen Source infoApache Version 2Open Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetJavaC++, JavaScript
Server operating systemsLinuxLinux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
OS X
Windows
Data schemeSchema-free and OWL/RDFS-schema supportyesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyes infosupports customizable data types and automatic typingyes
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.noyesyesno
Secondary indexesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.ANSI-99 for query and DML statements, subset of DDLSolr Parallel SQL Interfaceno
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Java API
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC++
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes (compute grid and cache interceptors can be used instead)Java pluginsyes
Triggersnoyes (cache interceptors and events)yes infoUser configurable commands triggered on index changesyes
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-Clusteryes (replicated cache)yesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyes (compute grid and hadoop accelerator)spark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlAccess rights for users and rolesSecurity Hooks for custom implementationsyesyes

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More resources
AnzoGraph DBGridGainSolrWakandaDB
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