DBMS > Adabas vs. Graph Engine vs. HBase vs. Microsoft Azure Synapse Analytics vs. SAP HANA

System Properties Comparison Adabas vs. Graph Engine vs. HBase vs. Microsoft Azure Synapse Analytics vs. SAP HANA

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

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Multivalue DBMS

Graph DBMS
Key-value store

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	3.58
Rank	#91	Overall
	#1	Multivalue DBMS

Score	0.62
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	31.25
Rank	#26	Overall
	#2	Wide column stores

Score	22.71
Rank	#30	Overall
	#18	Relational DBMS

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Website

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

www.graphengine.io

hbase.apache.org

azure.microsoft.com/services/synapse-analytics

www.sap.com/products/hana.html

Technical documentation

www.graphengine.io/docs/manual

hbase.apache.org/book.html

docs.microsoft.com/azure/synapse-analytics

help.sap.com/hana

Developer

Software AG

Microsoft

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Microsoft

SAP

Initial release

1971

2010

2008

2016

2010

Current release

2.3.4, January 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

.NET and C

Java

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

.NET

Linux
Unix
Windows

using Cygwin

hosted

Appliance or cloud-service

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

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

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

ADO.NET
JDBC
ODBC

JDBC
ODBC

Supported programming languages

Natural

C#
C++
F#
Visual Basic

C
C#
C++
Groovy
Java
PHP
Python
Scala

C#
Java
PHP

Server-side scripts

Stored procedures

in Natural

yes

Coprocessors in Java

Transact SQL

SQLScript, R

Triggers

yes

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

Sharding, horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

Single row ACID (across millions of columns)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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)

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

yes

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