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DBMS > EsgynDB vs. Greenplum vs. IBM Db2 Event Store vs. RDFox vs. Solr

System Properties Comparison EsgynDB vs. Greenplum vs. IBM Db2 Event Store vs. RDFox vs. Solr

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGreenplum  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRDFox  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Distributed Event Store optimized for Internet of Things use casesHigh performance knowledge graph and semantic reasoning engineA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSEvent Store
Time Series DBMS
Graph DBMS
RDF store
Search engine
Secondary database modelsDocument store
Spatial DBMS
Relational DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score8.08
Rank#48  Overall
#31  Relational DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.29
Rank#300  Overall
#24  Graph DBMS
#13  RDF stores
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.esgyn.cngreenplum.orgwww.ibm.com/­products/­db2-event-storewww.oxfordsemantic.techsolr.apache.org
Technical documentationdocs.greenplum.orgwww.ibm.com/­docs/­en/­db2-event-storedocs.oxfordsemantic.techsolr.apache.org/­resources.html
DeveloperEsgynPivotal Software Inc.IBMOxford Semantic TechnologiesApache Software Foundation
Initial release20152005201720172006
Current release7.0.0, September 20232.06.0, Septermber 20229.6.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial infofree developer edition availablecommercialOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaC and C++C++Java
Server operating systemsLinuxLinuxLinux infoLinux, macOS, Windows for the developer additionLinux
macOS
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyes infoRDF schemasyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyesyes infosupports customizable data types and automatic typing
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.noyes infosince Version 4.2noyes
Secondary indexesyesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyesyesyes infothrough the embedded Spark runtimenoSolr Parallel SQL Interface
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
RESTful HTTP API
SPARQL 1.1
Java API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC
Java
Perl
Python
R
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
Java
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresJava Stored ProceduresyesyesJava plugins
Triggersnoyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationActive-active shard replicationreplication via a shared file systemyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency in stand-alone mode, Eventual Consistency in replicated setupsEventual Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardRoles, resources, and access typesyes

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More resources
EsgynDBGreenplumIBM Db2 Event StoreRDFoxSolr
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