DBMS > Adabas vs. Bangdb vs. DolphinDB vs. Microsoft Azure Cosmos DB

System Properties Comparison Adabas vs. Bangdb vs. DolphinDB vs. Microsoft Azure Cosmos DB

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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

Converged and high performance database for device data, events, time series, document and graph

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Multivalue DBMS

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

Relational DBMS

Spatial DBMS

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

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

bangdb.com

www.dolphindb.com

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.bangdb.com

docs.dolphindb.cn/en/help200/index.html

learn.microsoft.com/azure/cosmos-db

Developer

Software AG

Sachin Sinha, BangDB

DolphinDB, Inc

Microsoft

Initial release

1971

2012

2018

2014

Current release

BangDB 2.0, October 2021

v2.00.4, January 2022

License

Commercial or Open Source

commercial

Open Source

BSD 3

commercial

free community version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C++

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux

Linux
Windows

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes

JSON types

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

secondary, composite, nested, reverse, geospatial

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

with add-on product Adabas SQL Gateway

SQL like support with command line tool

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

Proprietary protocol
RESTful HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

Natural

C
C#
C++
Java
Python

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

in Natural

yes

JavaScript

Triggers

yes, Notifications (with Streaming only)

JavaScript

Partitioning methods

Methods for storing different data on different nodes

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

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

horizontal partitioning

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

selectable replication factor, Knob for CAP (enterprise version only)

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

yes

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

User concepts

Access control

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

yes (enterprise version only)

Administrators, Users, Groups

Access rights can be defined down to the item level

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