DBMS > Fujitsu Enterprise Postgres vs. Microsoft Azure AI Search vs. NSDb vs. Spark SQL vs. Transbase

System Properties Comparison Fujitsu Enterprise Postgres vs. Microsoft Azure AI Search vs. NSDb vs. Spark SQL vs. Transbase

Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Search-as-a-service for web and mobile app development

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Spark SQL is a component on top of 'Spark Core' for structured data processing

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Document store
Spatial DBMS

Vector DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	5.59
Rank	#63	Overall
	#7	Search engines

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

www.postgresql.fastware.com

azure.microsoft.com/en-us/services/search

nsdb.io

spark.apache.org/sql

www.transaction.de/en/products/transbase.html

Technical documentation

www.postgresql.fastware.com/product-manuals

learn.microsoft.com/en-us/azure/search

nsdb.io/Architecture

spark.apache.org/docs/latest/sql-programming-guide.html

www.transaction.de/en/products/transbase/features.html

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Microsoft

Apache Software Foundation

Transaction Software GmbH

Initial release

2015

2017

2014

1987

Current release

Fujitsu Enterprise Postgres 14, January 2022

3.5.0 ( 2.13), September 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java, Scala

Scala

C and C++

Server operating systems

Linux
Windows

hosted

Linux
macOS

Linux
OS X
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

gRPC
HTTP REST
WebSocket

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C#
Java
JavaScript
Python

Java
Scala

Java
Python
R
Scala

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

Implicit feature of the cloud service

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

fine grained access rights according to SQL-standard

yes

using Azure authentication

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

Licensing and pricing models

Core based licensing
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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