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DBMS > Apache Phoenix vs. Hazelcast vs. Microsoft Azure Table Storage vs. Trino

System Properties Comparison Apache Phoenix vs. Hazelcast vs. Microsoft Azure Table Storage vs. Trino

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTrino  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA widely adopted in-memory data gridA Wide Column Store for rapid development using massive semi-structured datasetsFast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL
Primary database modelRelational DBMSKey-value storeWide column storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score5.72
Rank#59  Overall
#6  Key-value stores
Score3.55
Rank#80  Overall
#6  Wide column stores
Score5.28
Rank#61  Overall
#35  Relational DBMS
Websitephoenix.apache.orghazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tablestrino.io
Technical documentationphoenix.apache.orghazelcast.org/­imdg/­docstrino.io/­broadcast
trino.io/­docs/­current
DeveloperApache Software FoundationHazelcastMicrosoftTrino Software Foundation
Initial release2014200820122012 info2020 rebranded from PrestoSQL
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaJava
Server operating systemsLinux
Unix
Windows
All OS with a Java VMhostedLinux
macOS infofor devlopment
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesyesnodepending on connected data-source
SQL infoSupport of SQLyesSQL-like query languagenoyes
APIs and other access methodsJDBCJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIJDBC
RESTful HTTP API
Trino CLI
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor Servicesnoyes, depending on connected data-source
Triggersnoyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicedepending on connected data-source
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes infoReplicated Mapyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.depending on connected data-source
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistencydepending on connected data-source
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedoptimistic lockingdepending on connected data-source
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesdepending on connected data-source
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyRole-based access controlAccess rights based on private key authentication or shared access signaturesSQL standard access control
More information provided by the system vendor
Apache PhoenixHazelcastMicrosoft Azure Table StorageTrino
News

23 is a go, keeping pace with Java
17 September 2024

65: Performance boosts
12 September 2024

64: Control with Open Policy Agent OPA
22 August 2024

63: Querying with JS
1 August 2024

62: A lakehouse that simply works at Prezi
11 July 2024

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More resources
Apache PhoenixHazelcastMicrosoft Azure Table StorageTrino
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