DBMS > Adabas vs. Amazon DynamoDB vs. Apache Druid vs. Kyligence Enterprise vs. Spark SQL

System Properties Comparison Adabas vs. Amazon DynamoDB vs. Apache Druid vs. Kyligence Enterprise vs. Spark SQL

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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

A distributed analytics engine for big data, built on top of Apache Kylin

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

Primary database model

Multivalue DBMS

Document store
Key-value store

Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.46
Rank	#266	Overall
	#124	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

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

aws.amazon.com/dynamodb

druid.apache.org

kyligence.io/kyligence-enterprise

spark.apache.org/sql

Technical documentation

docs.aws.amazon.com/dynamodb

druid.apache.org/docs/latest/design

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

Developer

Software AG

Amazon

Apache Software Foundation and contributors

Kyligence, Inc.

Apache Software Foundation

Initial release

1971

2012

2016

2014

Current release

29.0.1, April 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

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

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

Implementation language

Java

Scala

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

hosted

Linux
OS X
Unix

Linux

Linux
OS X
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.

Secondary indexes

yes

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL for querying

ANSI SQL for queries (using Apache Calcite)

SQL-like DML and DDL statements

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

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

Supported programming languages

Natural

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java
Python
R
Scala

Server-side scripts

Stored procedures

in Natural

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

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

Sharding

manual/auto, time-based

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes

yes, via HDFS, S3 or other storage engines

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

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)

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

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

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