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DBMS > IBM Db2 Event Store vs. Neo4j vs. RavenDB vs. TigerGraph

System Properties Comparison IBM Db2 Event Store vs. Neo4j vs. RavenDB vs. TigerGraph

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Editorial information provided by DB-Engines
NameIBM Db2 Event Store  Xexclude from comparisonNeo4j  Xexclude from comparisonRavenDB  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionDistributed Event Store optimized for Internet of Things use casesScalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offeringsOpen Source Operational and Transactional Enterprise NoSQL Document DatabaseA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelEvent Store
Time Series DBMS
Graph DBMSDocument storeGraph DBMS
Secondary database modelsGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score44.46
Rank#23  Overall
#1  Graph DBMS
Score2.92
Rank#101  Overall
#18  Document stores
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitewww.ibm.com/­products/­db2-event-storeneo4j.comravendb.netwww.tigergraph.com
Technical documentationwww.ibm.com/­docs/­en/­db2-event-storeneo4j.com/­docsravendb.net/­docsdocs.tigergraph.com
DeveloperIBMNeo4j, Inc.Hibernating Rhinos
Initial release2017200720102017
Current release2.05.19, April 20245.4, July 2022
License infoCommercial or Open Sourcecommercial infofree developer edition availableOpen Source infoGPL version3, commercial licenses availableOpen Source infoAGPL version 3, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Neo4j Aura: Neo4j’s fully managed cloud service: The zero-admin, always-on graph database for cloud developers.
Implementation languageC and C++Java, ScalaC#C++
Server operating systemsLinux infoLinux, macOS, Windows for the developer additionLinux infoCan also be used server-less as embedded Java database.
OS X
Solaris
Windows
Linux
macOS
Raspberry Pi
Windows
Linux
Data schemeyesschema-free and schema-optionalschema-freeyes
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.nono
Secondary indexesnoyes infopluggable indexing subsystem, by default Apache Luceneyes
SQL infoSupport of SQLyes infothrough the embedded Spark runtimenoSQL-like query language (RQL)SQL-like query language (GSQL)
APIs and other access methodsADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Bolt protocol
Cypher query language
Java API
Neo4j-OGM infoObject Graph Mapper
RESTful HTTP API
Spring Data Neo4j
TinkerPop 3
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.Net
Clojure
Elixir
Go
Groovy
Haskell
Java
JavaScript
Perl
PHP
Python
Ruby
Scala
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Server-side scripts infoStored proceduresyesyes infoUser defined Procedures and Functionsyesyes
Triggersnoyes infovia event handleryesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes using Neo4j FabricSharding
Replication methods infoMethods for redundantly storing data on multiple nodesActive-active shard replicationCausal Clustering using Raft protocol infoavailable in in Enterprise Version onlyMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyCausal and Eventual Consistency configurable in Causal Cluster setup
Immediate Consistency in stand-alone mode
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynoyes infoRelationships in graphsnoyes infoRelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID, Cluster-wide transaction availableACID
Concurrency infoSupport for concurrent manipulation of dataNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers, roles and permissions. Pluggable authentication with supported standards (LDAP, Active Directory, Kerberos)Authorization levels configured per client per databaseRole-based access control
More information provided by the system vendor
IBM Db2 Event StoreNeo4jRavenDBTigerGraph
Specific characteristicsNeo4j delivers graph technology that has been battle tested for performance and scale...
» more
Competitive advantagesNeo4j is the market leader, graph database category creator, and the most widely...
» more
Typical application scenariosReal-Time Recommendations Master Data Management Identity and Access Management Network...
» more
Key customersOver 800 commercial customers and over 4300 startups use Neo4j. Flagship customers...
» more
Market metricsNeo4j boasts the world's largest graph database ecosystem with more than 140 million...
» more
Licensing and pricing modelsGPL v3 license that can be used all the places where you might use MySQL. Neo4j Commercial...
» more
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