DBMS > Adabas vs. Databricks vs. EJDB vs. LeanXcale

System Properties Comparison Adabas vs. Databricks vs. EJDB vs. LeanXcale

Please select another system to include it in the comparison.

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

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.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Primary database model

Multivalue DBMS

Document store
Relational DBMS

Document store

Key-value store
Relational DBMS

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	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Website

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

www.databricks.com

github.com/Softmotions/ejdb

www.leanxcale.com

Technical documentation

docs.databricks.com

github.com/Softmotions/ejdb/blob/master/README.md

Developer

Software AG

Databricks

Softmotions

LeanXcale

Initial release

1971

2013

2012

2015

License

Commercial or Open Source

commercial

Open Source

GPLv2

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

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

server-less

Data scheme

yes

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

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

through Apache Derby

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

in-process shared library

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Supported programming languages

Natural

Python
R
Scala

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
Java
Scala

Server-side scripts

Stored procedures

in Natural

user defined functions and aggregates

Triggers

Partitioning methods

Methods for storing different data on different nodes

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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)

More information provided by the system vendor

Specific characteristics

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

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

PostgreSQL is the DBMS of the Year 2023
2 January 2024, Matthias Gelbmann, Paul Andlinger

show all

Recent citations in the news

Re-evaluating legacy: Should you leave Adabas (and Natural) behind?
30 May 2024, ITWeb

State agency proves DevOps and mainframes can coexist
12 April 2024, SiliconANGLE News

Is it the end of the road for Software AG after selling its integration business to IBM?
12 January 2024, diginomica

IBM buys 50-year-old Software AG's enterprise tech units for €2.13B in cash
18 December 2023, The Register

Michael E. Jakes Obituary (1941 - 2023)
26 October 2023, Legacy.com

provided by Google News

Qlik Introduces More Rapid Enterprise AI Adoption Through New Integration with Databricks AI Functions
11 June 2024, Yahoo Finance

Protecto Announces Data Security and Safety Guardrails for Gen AI Apps in Databricks
11 June 2024, PR Newswire

Informatica expands Databricks partnership to tackle expanding AI workloads – Blocks and Files
11 June 2024, Blocks and Files

Why Databricks' Tabular Play Has Put Snowflake On The Defensive
10 June 2024, Forbes

Snowflake, DataBricks and the Fight for Apache Iceberg Tables
10 June 2024, The New Stack

provided by Google News

Share this page