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DBMS > Datomic vs. Dgraph vs. EsgynDB vs. IBM Db2 Event Store vs. Solr

System Properties Comparison Datomic vs. Dgraph vs. EsgynDB vs. IBM Db2 Event Store vs. Solr

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionDistributed Event Store optimized for Internet of Things use casesA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSGraph DBMSRelational DBMSEvent Store
Time Series DBMS
Search engine
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.datomic.comdgraph.iowww.esgyn.cnwww.ibm.com/­products/­db2-event-storesolr.apache.org
Technical documentationdocs.datomic.comdgraph.io/­docswww.ibm.com/­docs/­en/­db2-event-storesolr.apache.org/­resources.html
DeveloperCognitectDgraph Labs, Inc.EsgynIBMApache Software Foundation
Initial release20122016201520172006
Current release1.0.6735, June 20232.09.6.0, April 2024
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0commercialcommercial infofree developer edition availableOpen 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 languageJava, ClojureGoC++, JavaC and C++Java
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
LinuxLinux infoLinux, macOS, Windows for the developer additionAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesschema-freeyesyesyes 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.nonononoyes
Secondary indexesyesyesyesnoyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnonoyesyes infothrough the embedded Spark runtimeSolr Parallel SQL Interface
APIs and other access methodsRESTful HTTP APIGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP/JSON API
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresyes infoTransaction FunctionsnoJava Stored ProceduresyesJava plugins
TriggersBy using transaction functionsnononoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersSynchronous replication via RaftMulti-source replication between multi datacentersActive-active shard replicationyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesnospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDnooptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesNo - written data is immutableyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyesyes
User concepts infoAccess controlnono infoPlanned for future releasesfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes

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More resources
DatomicDgraphEsgynDBIBM Db2 Event StoreSolr
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