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DBMS > Fauna vs. Fujitsu Enterprise Postgres vs. Netezza vs. WakandaDB

System Properties Comparison Fauna vs. Fujitsu Enterprise Postgres vs. Netezza vs. WakandaDB

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Editorial information provided by DB-Engines
NameFauna infopreviously named FaunaDB  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionFauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Data warehouse and analytics appliance part of IBM PureSystemsWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Graph DBMS
Relational DBMS
Time Series DBMS
Relational DBMSRelational DBMSObject oriented DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.52
Rank#153  Overall
#26  Document stores
#14  Graph DBMS
#71  Relational DBMS
#13  Time Series DBMS
Score0.31
Rank#285  Overall
#129  Relational DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitefauna.comwww.postgresql.fastware.comwww.ibm.com/­products/­netezzawakanda.github.io
Technical documentationdocs.fauna.comwww.postgresql.fastware.com/­product-manualswakanda.github.io/­doc
DeveloperFauna, Inc.PostgreSQL Global Development Group, Fujitsu Australia Software TechnologyIBMWakanda SAS
Initial release201420002012
Current releaseFujitsu Enterprise Postgres 14, January 20222.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaCC++, JavaScript
Server operating systemshostedLinux
Windows
Linux infoincluded in applianceLinux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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.nono
Secondary indexesyesyesyes
SQL infoSupport of SQLnoyesyesno
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
OLE DB
RESTful HTTP API
Supported programming languagesC#
Go
Java
JavaScript
Python
Ruby
Scala
Swift
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Fortran
Java
Lua
Perl
Python
R
JavaScript
Server-side scripts infoStored proceduresuser defined functionsuser defined functionsyesyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning infoconsistent hashingpartitioning by range, list and by hashShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.nono
User concepts infoAccess controlIdentity management, authentication, and access controlfine grained access rights according to SQL-standardUsers with fine-grained authorization conceptyes
More information provided by the system vendor
Fauna infopreviously named FaunaDBFujitsu Enterprise PostgresNetezza infoAlso called PureData System for Analytics by IBMWakandaDB
Specific characteristics100% compatible with community PostgreSQL
» more
Competitive advantagesBuilt-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more
Typical application scenariosTransactional payments applications, reporting and mixed workloads.
» more
Market metricsOver 30 years experience in database technology. Over 20 years in Postgres development...
» more
Licensing and pricing modelsCore based licensing
» more

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More resources
Fauna infopreviously named FaunaDBFujitsu Enterprise PostgresNetezza infoAlso called PureData System for Analytics by IBMWakandaDB
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