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DBMS > Hazelcast vs. Newts vs. Tarantool vs. XTDB

System Properties Comparison Hazelcast vs. Newts vs. Tarantool vs. XTDB

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonNewts  Xexclude from comparisonTarantool  Xexclude from comparisonXTDB infoformerly named Crux  Xexclude from comparison
DescriptionA widely adopted in-memory data gridTime Series DBMS based on CassandraIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelKey-value storeTime Series DBMSDocument store
Key-value store
Relational DBMS
Document store
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
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.11
Rank#343  Overall
#46  Document stores
Websitehazelcast.comopennms.github.io/­newtswww.tarantool.iogithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationhazelcast.org/­imdg/­docsgithub.com/­OpenNMS/­newts/­wikiwww.tarantool.io/­en/­docwww.xtdb.com/­docs
DeveloperHazelcastOpenNMS GroupVKJuxt Ltd.
Initial release2008201420082019
Current release5.3.6, November 20232.10.0, May 20221.19, September 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++Clojure
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
BSD
Linux
macOS
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeschema-freeFlexible 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, extensible-data-notation format
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.yes infothe object must implement a serialization strategynonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like query languagenoFull-featured ANSI SQL supportlimited SQL, making use of Apache Calcite
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
HTTP REST
Java API
Open binary protocolHTTP REST
JDBC
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
JavaC
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Clojure
Java
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesnoLua, C and SQL stored proceduresno
Triggersyes infoEventsnoyes, before/after data modification events, on replication events, client session eventsno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.none
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapselectable replication factor infobased on CassandraAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Casual 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 integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlRole-based access controlnoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
HazelcastNewtsTarantoolXTDB infoformerly named Crux
DB-Engines blog posts

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

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