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. Spark SQL vs. VoltDB vs. WakandaDB vs. Yanza

System Properties Comparison Apache Phoenix vs. Spark SQL vs. VoltDB vs. WakandaDB vs. Yanza

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonSpark SQL  Xexclude from comparisonVoltDB  Xexclude from comparisonWakandaDB  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseSpark SQL is a component on top of 'Spark Core' for structured data processingDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memoryWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access dataTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSObject oriented DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score1.47
Rank#157  Overall
#73  Relational DBMS
Score0.10
Rank#356  Overall
#16  Object oriented DBMS
Websitephoenix.apache.orgspark.apache.org/­sqlwww.voltdb.comwakanda.github.ioyanza.com
Technical documentationphoenix.apache.orgspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.voltdb.comwakanda.github.io/­doc
DeveloperApache Software FoundationApache Software FoundationVoltDB Inc.Wakanda SASYanza
Initial release20142014201020122015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20193.5.0 ( 2.13), September 202311.3, April 20222.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro EditionsOpen Source infoAGPLv3, extended commercial license availablecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaJava, C++C++, JavaScript
Server operating systemsLinux
Unix
Windows
Linux
OS X
Windows
Linux
OS X infofor development
Linux
OS X
Windows
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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.nononono
Secondary indexesyesnoyesno
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infoonly a subset of SQL 99nono
APIs and other access methodsJDBCJDBC
ODBC
Java API
JDBC
RESTful HTTP/JSON API
RESTful HTTP APIHTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
Java
Python
R
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
JavaScriptany language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsnoJavayesno
Triggersnononoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
nonenone
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infoFOREIGN KEY constraints are not supportedno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoTransactions are executed single-threaded within stored proceduresACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoData access is serialized by the serveryesyes
Durability infoSupport for making data persistentyesyesyes infoSnapshots and command loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancynoUsers and roles with access to stored proceduresyesno

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 PhoenixSpark SQLVoltDBWakandaDBYanza
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

Azure #HDInsight Apache Phoenix now supports Zeppelin
16 August 2018, Microsoft

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

Apache Calcite, FreeMarker, Gora, Phoenix, and Solr updated
27 March 2017, SDTimes.com

Azure HDInsight Analytics Platform Now Supports Apache Hadoop 3.0
18 April 2019, eWeek

provided by Google News

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

What is Apache Spark? The big data platform that crushed Hadoop
3 April 2024, InfoWorld

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

Performant IPv4 Range Spark Joins | by Jean-Claude Cote
24 January 2024, Towards Data Science

Simba Technologies(R) Introduces New, Powerful JDBC Driver With SQL Connector for Apache Spark(TM)
17 March 2024, Yahoo Singapore News

provided by Google News

Unveiling Volt Active Data's game-changing approach to limitless app performance
16 October 2023, YourStory

 VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Turns to Real-Time Analytics with NewSQL Database
30 January 2014, Datanami

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

provided by Google News



Share this page

Featured Products

Neo4j logo

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

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

Present your product here