DBMS > Adabas vs. AlaSQL vs. Apache Druid vs. Google BigQuery vs. Ignite

System Properties Comparison Adabas vs. AlaSQL vs. Apache Druid vs. Google BigQuery vs. Ignite

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

JavaScript DBMS library

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Large scale data warehouse service with append-only tables

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.

Primary database model

Multivalue DBMS

Document store
Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

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

alasql.org

druid.apache.org

cloud.google.com/bigquery

ignite.apache.org

Technical documentation

github.com/AlaSQL/alasql

druid.apache.org/docs/latest/design

cloud.google.com/bigquery/docs

apacheignite.readme.io/docs

Developer

Software AG

Andrey Gershun & Mathias R. Wulff

Apache Software Foundation and contributors

Google

Apache Software Foundation

Initial release

1971

2014

2012

2010

2015

Current release

29.0.1, April 2024

Apache Ignite 2.6

License

Commercial or Open Source

commercial

Open Source

MIT-License

Open Source

Apache license v2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Java

C++, Java, .Net

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Unix

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

schema-less columns are supported

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL for querying

yes

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

JavaScript API

JDBC
RESTful HTTP/JSON API

RESTful HTTP/JSON API

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

Supported programming languages

Natural

JavaScript

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

in Natural

user defined functions

in JavaScript

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

Triggers

yes

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

none

Sharding

manual/auto, time-based

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

yes, via HDFS, S3 or other storage engines

yes (replicated cache)

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

only for local storage and DOM-storage

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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)

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Security Hooks for custom implementations

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