DBMS > Adabas vs. Drizzle vs. Spark SQL vs. Transwarp StellarDB

System Properties Comparison Adabas vs. Drizzle vs. Spark SQL vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

used typically together with the Natural programming platform

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Multivalue DBMS

Relational DBMS

Graph DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

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

spark.apache.org/sql

www.transwarp.cn/en/product/stellardb

Technical documentation

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

Developer

Software AG

Drizzle project, originally started by Brian Aker

Apache Software Foundation

Transwarp

Initial release

1971

2008

2014

Current release

7.2.4, September 2012

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

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

FreeBSD
Linux
OS X

Linux
OS X
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

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

yes

with proprietary extensions

SQL-like DML and DDL statements

SQL-like query language

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

JDBC
ODBC

OpenCypher

Supported programming languages

Natural

C
C++
Java
PHP

Java
Python
R
Scala

Server-side scripts

Stored procedures

in Natural

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

yes, utilizing Spark Core

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

Multi-source replication
Source-replica replication

none

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

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.

User concepts

Access control

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

yes

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