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. Fujitsu Enterprise Postgres vs. Spark SQL vs. VoltDB vs. WakandaDB

System Properties Comparison Apache Phoenix vs. Fujitsu Enterprise Postgres vs. Spark SQL vs. VoltDB vs. WakandaDB

Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonSpark SQL  Xexclude from comparisonVoltDB  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Spark 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 data
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score0.37
Rank#278  Overall
#128  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.orgwww.postgresql.fastware.comspark.apache.org/­sqlwww.voltdb.comwakanda.github.io
Technical documentationphoenix.apache.orgwww.postgresql.fastware.com/­product-manualsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.voltdb.comwakanda.github.io/­doc
DeveloperApache Software FoundationPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyApache Software FoundationVoltDB Inc.Wakanda SAS
Initial release2014201420102012
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 2019Fujitsu Enterprise Postgres 14, January 20223.5.0 ( 2.13), September 202311.3, April 20222.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache 2.0Open Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro EditionsOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCScalaJava, C++C++, JavaScript
Server operating systemsLinux
Unix
Windows
Linux
Windows
Linux
OS X
Windows
Linux
OS X infofor development
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLyesyesSQL-like DML and DDL statementsyes infoonly a subset of SQL 99no
APIs and other access methodsJDBCADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Java API
JDBC
RESTful HTTP/JSON API
RESTful HTTP API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
JavaScript
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsnoJavayes
Triggersnoyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashyes, utilizing Spark CoreShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationnoneMulti-source replication
Source-replica replication
none
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 integritynoyesnono infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID infoTransactions are executed single-threaded within stored proceduresACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes infoData access is serialized by the serveryes
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command loggingyes
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-tenancyfine grained access rights according to SQL-standardnoUsers and roles with access to stored proceduresyes

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 PhoenixFujitsu Enterprise PostgresSpark SQLVoltDBWakandaDB
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, azure.microsoft.com

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

Fujitsu Develops Column-Oriented Data-Processing Engine Enabling Fast, High-Volume Data Analysis in Database ...
26 February 2015, Fujitsu

Expert Insight 202009 KAC
4 September 2023, Fujitsu

Fujitsu recognized as winner of 2023 Microsoft Japan Healthcare & Life Sciences Partner of the Year Award for its ...
28 June 2023, Fujitsu

Primary Data says stop, Hammerspace, Innodisk cooks some SSDs, and Fujitsu goes blockchain
22 May 2018, The Register

DCPMM
1 August 2020, Fujitsu

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

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 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

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

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

Present your product here