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DBMS > EXASOL vs. Hazelcast vs. Tarantool vs. VoltDB

System Properties Comparison EXASOL vs. Hazelcast vs. Tarantool vs. VoltDB

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonHazelcast  Xexclude from comparisonTarantool  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A widely adopted in-memory data gridIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelRelational DBMSKey-value storeDocument store
Key-value store
Relational DBMS
Relational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.25
Rank#120  Overall
#57  Relational DBMS
Score6.87
Rank#55  Overall
#6  Key-value stores
Score1.67
Rank#150  Overall
#25  Document stores
#25  Key-value stores
#69  Relational DBMS
Score1.46
Rank#159  Overall
#74  Relational DBMS
Websitewww.exasol.comhazelcast.comwww.tarantool.iowww.voltdb.com
Technical documentationwww.exasol.com/­resourceshazelcast.org/­imdg/­docswww.tarantool.io/­en/­docdocs.voltdb.com
DeveloperExasolHazelcastVKVoltDB Inc.
Initial release2000200820082010
Current release5.3.6, November 20232.10.0, May 202211.3, April 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC and C++Java, C++
Server operating systemsAll OS with a Java VMBSD
Linux
macOS
Linux
OS X infofor development
Data schemeyesschema-freeFlexible 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.noyes infothe object must implement a serialization strategyno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like query languageFull-featured ANSI SQL supportyes infoonly a subset of SQL 99
APIs and other access methods.Net
JDBC
ODBC
WebSocket
JCache
JPA
Memcached protocol
RESTful HTTP API
Open binary protocolJava API
JDBC
RESTful HTTP/JSON API
Supported programming languagesJava
Lua
Python
R
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor ServicesLua, C and SQL stored proceduresJava
Triggersyesyes infoEventsyes, 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 nodesyes infoReplicated MapAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmCasual 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
Foreign keys infoReferential integrityyesnoyesno infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes infoSnapshots and command logging
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 persistence
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardRole-based access controlAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
Users and roles with access to stored procedures

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More resources
EXASOLHazelcastTarantoolVoltDB
DB-Engines blog posts

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

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