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DBMS > Apache Phoenix vs. Hazelcast vs. Tarantool vs. Warp 10

System Properties Comparison Apache Phoenix vs. Hazelcast vs. Tarantool vs. Warp 10

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHazelcast  Xexclude from comparisonTarantool  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA widely adopted in-memory data gridIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMSKey-value storeDocument store
Key-value store
Relational DBMS
Time Series 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
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitephoenix.apache.orghazelcast.comwww.tarantool.iowww.warp10.io
Technical documentationphoenix.apache.orghazelcast.org/­imdg/­docswww.tarantool.io/­en/­docwww.warp10.io/­content/­02_Getting_started
DeveloperApache Software FoundationHazelcastVKSenX
Initial release2014200820082015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.3.6, November 20232.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availableOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache License 2.0
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++Java
Server operating systemsLinux
Unix
Windows
All OS with a Java VMBSD
Linux
macOS
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-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
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 strategynono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesSQL-like query languageFull-featured ANSI SQL supportno
APIs and other access methodsJDBCJCache
JPA
Memcached protocol
RESTful HTTP API
Open binary protocolHTTP API
Jupyter
WebSocket
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor ServicesLua, C and SQL stored proceduresyes infoWarpScript
Triggersnoyes 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 infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoReplicated MapAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual 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
Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynonoyesno
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 transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyes, 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 persistenceyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyRole-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
Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache PhoenixHazelcastTarantoolWarp 10
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