DBMS > LeanXcale vs. Microsoft Azure Synapse Analytics vs. PostGIS vs. Trafodion

System Properties Comparison LeanXcale vs. Microsoft Azure Synapse Analytics vs. PostGIS vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Spatial extension of PostgreSQL

Transactional SQL-on-Hadoop DBMS

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

www.leanxcale.com

azure.microsoft.com/services/synapse-analytics

postgis.net

trafodion.apache.org

Technical documentation

docs.microsoft.com/azure/synapse-analytics

postgis.net/documentation

trafodion.apache.org/documentation.html

Developer

LeanXcale

Microsoft

Apache Software Foundation, originally developed by HP

Initial release

2015

2016

2005

2014

Current release

3.4.2, February 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPL v2.0

Open Source

Apache 2.0

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

C++

C++, Java

Server operating systems

hosted

Linux

Data scheme

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through Apache Derby

yes

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
ODBC

Supported programming languages

C
Java
Scala

C#
Java
PHP

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

Transact SQL

user defined functions

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

yes

based on PostgreSQL

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on PostgreSQL

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

yes

based on PostgreSQL

fine grained access rights according to SQL-standard

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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