DBMS > Adabas vs. Amazon Redshift vs. Microsoft Azure Synapse Analytics vs. Spark SQL vs. TDengine

System Properties Comparison Adabas vs. Amazon Redshift vs. Microsoft Azure Synapse Analytics vs. Spark SQL vs. TDengine

Editorial information provided by DB-Engines

Name

Description

OLTP - DBMS for mainframes and Linux/Unix/Windows environments

used typically together with the Natural programming platform

Large scale data warehouse service for use with business intelligence tools

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

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

Time Series DBMS and big data platform

Primary database model

Multivalue DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

www.softwareag.com/en_corporate/platform/adabas-natural.html

aws.amazon.com/redshift

azure.microsoft.com/services/synapse-analytics

spark.apache.org/sql

github.com/taosdata/TDengine
tdengine.com

Technical documentation

docs.aws.amazon.com/redshift

docs.microsoft.com/azure/synapse-analytics

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

docs.tdengine.com

Developer

Software AG

Amazon (based on PostgreSQL)

Microsoft

Apache Software Foundation

TDEngine, previously Taos Data

Initial release

1971

2012

2016

2014

2019

Current release

3.5.0 ( 2.13), September 2023

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

AGPL V3, also commercial editions available

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++

Scala

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
OS X
Windows

Linux
Windows

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.

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

does not fully support an SQL-standard

yes

SQL-like DML and DDL statements

Standard SQL with extensions for time-series applications

APIs and other access methods

HTTP API

with add-on software Adabas SOA Gateway
SOAP-based API

with add-on software Adabas SOA Gateway

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

Natural

All languages supporting JDBC/ODBC

C#
Java
PHP

Java
Python
R
Scala

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

in Natural

user defined functions

in Python

Transact SQL

Triggers

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

yes, with additonal products like Adabas Cluster Services, Adabas Parallel Services, Adabas Vista

Sharding

Sharding, horizontal partitioning

yes, utilizing Spark Core

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

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

only with OS-specific tools (e.g. IBM RACF, CA Top Secret)

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

Specific characteristics

TDengine™ is a next generation data historian purpose-built for Industry 4.0 and...
» more

Competitive advantages

High Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more

Typical application scenarios

TDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more

Market metrics

TDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more

Licensing and pricing models

TDengine OSS is an open source, cloud native time series database. It includes built-in...
» more

News

Compare InfluxDB vs. TDengine
19 April 2024

Why We Need the Next Generation Data Historian
15 April 2024

Is Closed-Source Software Really More Secure?
8 April 2024

Developers: Stop Donating Your Work to Cloud Service Providers!
28 March 2024

Compare AVEVA Data Hub vs. TDengine
19 March 2024

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.