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DBMS > Datomic vs. IBM Db2 Event Store vs. Tarantool vs. ToroDB

System Properties Comparison Datomic vs. IBM Db2 Event Store vs. Tarantool vs. ToroDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonTarantool  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityDistributed Event Store optimized for Internet of Things use casesIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSEvent Store
Time Series DBMS
Document store
Key-value store
Relational DBMS
Document store
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.27
Rank#309  Overall
#2  Event Stores
#28  Time Series DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.datomic.comwww.ibm.com/­products/­db2-event-storewww.tarantool.iogithub.com/­torodb/­server
Technical documentationdocs.datomic.comwww.ibm.com/­docs/­en/­db2-event-storewww.tarantool.io/­en/­doc
DeveloperCognitectIBMVK8Kdata
Initial release2012201720082016
Current release1.0.7075, December 20232.02.10.0, May 2022
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infofree developer edition availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC and C++C and C++Java
Server operating systemsAll OS with a Java VMLinux infoLinux, macOS, Windows for the developer additionBSD
Linux
macOS
All OS with a Java 7 VM
Data schemeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsschema-free
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes infostring, integer, double, boolean, date, object_id
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
Secondary indexesyesnoyes
SQL infoSupport of SQLnoyes infothrough the embedded Spark runtimeFull-featured ANSI SQL support
APIs and other access methodsRESTful HTTP APIADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Open binary protocol
Supported programming languagesClojure
Java
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresyes infoTransaction FunctionsyesLua, C and SQL stored procedures
TriggersBy using transaction functionsnoyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersActive-active shard replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsno
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyes, write ahead loggingyes
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 developmentyesyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Access rights for users and roles

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More resources
DatomicIBM Db2 Event StoreTarantoolToroDB
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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