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DBMS > EXASOL vs. IBM Db2 Event Store vs. Tarantool vs. Trafodion

System Properties Comparison EXASOL vs. IBM Db2 Event Store vs. Tarantool vs. Trafodion

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonTarantool  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Distributed Event Store optimized for Internet of Things use casesIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsTransactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSEvent Store
Time Series DBMS
Document store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitewww.exasol.comwww.ibm.com/­products/­db2-event-storewww.tarantool.iotrafodion.apache.org
Technical documentationwww.exasol.com/­resourceswww.ibm.com/­docs/­en/­db2-event-storewww.tarantool.io/­en/­doctrafodion.apache.org/­documentation.html
DeveloperExasolIBMVKApache Software Foundation, originally developed by HP
Initial release2000201720082014
Current release2.02.10.0, May 20222.3.0, February 2019
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC and C++C and C++C++, Java
Server operating systemsLinux infoLinux, macOS, Windows for the developer additionBSD
Linux
macOS
Linux
Data schemeyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyesstring, double, decimal, uuid, integer, blob, boolean, datetimeyes
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 indexesyesnoyesyes
SQL infoSupport of SQLyesyes infothrough the embedded Spark runtimeFull-featured ANSI SQL supportyes
APIs and other access methods.Net
JDBC
ODBC
WebSocket
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
Open binary protocolADO.NET
JDBC
ODBC
Supported programming languagesJava
Lua
Python
R
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
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresuser defined functionsyesLua, C and SQL stored proceduresJava Stored Procedures
Triggersyesnoyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, 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 nodesActive-active shard replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnoyes infovia user defined functions and HBase
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
Immediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
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 transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesYes - 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.yesyesyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardfine 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
fine grained access rights according to SQL-standard

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More resources
EXASOLIBM Db2 Event StoreTarantoolTrafodion
DB-Engines blog posts

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

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