DBMS > Adabas vs. Apache Doris vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. Microsoft Azure Table Storage

System Properties Comparison Adabas vs. Apache Doris vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. Microsoft Azure Table Storage

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

An MPP-based analytics DBMS embracing the MySQL protocol

Globally distributed, horizontally scalable, multi-model database service

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

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Multivalue DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Wide column store

Secondary database models

Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	20.56
Rank	#31	Overall
	#19	Relational DBMS

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Website

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

doris.apache.org
github.com/apache/doris

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/services/synapse-analytics

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

github.com/apache/doris/wiki

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/azure/synapse-analytics

Developer

Software AG

Apache Software Foundation, originally contributed from Baidu

Microsoft

Initial release

1971

2017

2014

2016

2012

Current release

1.2.2, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

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

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

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 properties auto-indexed by default

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

SQL-like query language

yes

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
MySQL client

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC

RESTful HTTP API

Supported programming languages

Natural

Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
Java
PHP

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Server-side scripts

Stored procedures

in Natural

user defined functions

JavaScript

Transact SQL

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

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

horizontal partitioning

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Multi-item ACID transactions with snapshot isolation within a partition

ACID

optimistic locking

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.

User concepts

Access control

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

yes

Access rights based on private key authentication or shared access signatures

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