DBMS > Adabas vs. Databricks vs. Drizzle vs. Ignite vs. RocksDB

System Properties Comparison Adabas vs. Databricks vs. Drizzle vs. Ignite vs. RocksDB

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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Multivalue DBMS

Document store
Relational DBMS

Relational DBMS

Key-value store
Relational DBMS

Key-value store

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

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

www.databricks.com

ignite.apache.org

rocksdb.org

Technical documentation

docs.databricks.com

apacheignite.readme.io/docs

github.com/facebook/rocksdb/wiki

Developer

Software AG

Databricks

Drizzle project, originally started by Brian Aker

Apache Software Foundation

Facebook, Inc.

Initial release

1971

2013

2008

2015

2013

Current release

7.2.4, September 2012

Apache Ignite 2.6

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

GNU GPL

Open Source

Apache 2.0

Open Source

BSD

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, .Net

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

FreeBSD
Linux
OS X

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

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

with add-on product Adabas SQL Gateway

with Databricks SQL

yes

with proprietary extensions

ANSI-99 for query and DML statements, subset of DDL

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
RESTful HTTP API

JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

C++ API
Java API

Supported programming languages

Natural

Python
R
Scala

C
C++
Java
PHP

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

in Natural

user defined functions and aggregates

yes (compute grid and cache interceptors can be used instead)

Triggers

hooks for callbacks inside the server can be used.

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

Multi-source replication
Source-replica replication

yes (replicated cache)

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

yes

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)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Security Hooks for custom implementations

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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