DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Phoenix vs. InfinityDB vs. TempoIQ vs. Vitess

System Properties Comparison Apache Phoenix vs. InfinityDB vs. TempoIQ vs. Vitess

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonInfinityDB  Xexclude from comparisonTempoIQ infoformerly TempoDB  Xexclude from comparisonVitess  Xexclude from comparison
TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA Java embedded Key-Value Store which extends the Java Map interfaceScalable analytics DBMS for sensor data, provided as a service (SaaS)Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSKey-value storeTime Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitephoenix.apache.orgboilerbay.comtempoiq.com (offline)vitess.io
Technical documentationphoenix.apache.orgboilerbay.com/­infinitydb/­manualvitess.io/­docs
DeveloperApache Software FoundationBoiler Bay Inc.TempoIQThe Linux Foundation, PlanetScale
Initial release2014200220122013
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.015.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoApache Version 2.0, commercial licenses available
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 languageJavaJavaGo
Server operating systemsLinux
Unix
Windows
All OS with a Java VMDocker
Linux
macOS
Data schemeyes infolate-bound, schema-on-read capabilitiesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.nonono
Secondary indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyes
SQL infoSupport of SQLyesnonoyes infowith proprietary extensions
APIs and other access methodsJDBCAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
HTTP APIADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
JavaC#
Java
JavaScript infoNode.js
Python
Ruby
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsnonoyes infoproprietary syntax
Triggersnonoyes infoRealtime Alertsyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency infoREAD-COMMITTED or SERIALIZEDEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilitynoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsnoACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynosimple authentication-based access controlUsers with fine-grained authorization concept infono user groups or roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache PhoenixInfinityDBTempoIQ infoformerly TempoDBVitess
DB-Engines blog posts

Cloudera's HBase PaaS offering now supports Complex Transactions
11 August 2021,  Krishna Maheshwari (sponsor) 

show all

Recent citations in the news

Supercharge SQL on Your Data in Apache HBase with Apache Phoenix | Amazon Web Services
2 June 2016, AWS Blog

Bridge the SQL-NoSQL gap with Apache Phoenix
4 February 2016, InfoWorld

Hortonworks Starts Hadoop Summit with Data Platform Update -- ADTmag
28 June 2016, ADT Magazine

Deep dive into Azure HDInsight 4.0
25 September 2018, azure.microsoft.com

Amazon EMR 4.7.0 – Apache Tez & Phoenix, Updates to Existing Apps | Amazon Web Services
2 June 2016, AWS Blog

provided by Google News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

With Vitess 4.0, database vendor matures cloud-native platform
13 November 2019, TechTarget

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Present your product here