DBMS > Adabas vs. Apache Druid vs. GridDB vs. MongoDB vs. SiteWhere

System Properties Comparison Adabas vs. Apache Druid vs. GridDB vs. MongoDB vs. SiteWhere

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

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

Scalable in-memory time series database optimized for IoT and Big Data

One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure

M2M integration platform for persisting/querying time series data

Primary database model

Multivalue DBMS

Relational DBMS
Time Series DBMS

Time Series DBMS

Document store

Time Series DBMS

Secondary database models

Key-value store
Relational DBMS

Spatial DBMS
Search engine

integrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS

Time Series Collections introduced in Release 5.0
Vector DBMS

currently available in the MongoDB Atlas cloud service only

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

Score	3.17
Rank	#94	Overall
	#1	Multivalue DBMS

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

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	421.65
Rank	#5	Overall
	#1	Document stores

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

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

druid.apache.org

griddb.net

www.mongodb.com

github.com/sitewhere/sitewhere

Technical documentation

druid.apache.org/docs/latest/design

docs.griddb.net

www.mongodb.com/docs/manual

sitewhere1.sitewhere.io/index.html

Developer

Software AG

Apache Software Foundation and contributors

Toshiba Corporation

MongoDB, Inc

SiteWhere

Initial release

1971

2012

2013

2009

2010

Current release

29.0.1, April 2024

5.1, August 2022

6.0.7, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache license v2

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

MongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.

Open Source

Common Public Attribution License Version 1.0

Cloud-based only

Only available as a cloud service

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

Java

C++

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

Linux
OS X
Unix

Linux

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free

Although schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.

predefined scheme

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

string, integer, double, decimal, boolean, date, object_id, geospatial

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

SQL92, SQL-like TQL (Toshiba Query Language)

Read-only SQL queries via the MongoDB Atlas SQL Interface

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
RESTful HTTP/JSON API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

HTTP REST

Supported programming languages

Natural

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Actionscript

unofficial driver
C
C#
C++
Clojure

unofficial driver
ColdFusion

unofficial driver
D

unofficial driver
Dart

unofficial driver
Delphi

unofficial driver
Erlang
Go
Groovy

unofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp

unofficial driver
Lua

unofficial driver
MatLab

unofficial driver
Perl
PHP
PowerShell

unofficial driver
Prolog

unofficial driver
Python
R

unofficial driver
Ruby
Rust
Scala
Smalltalk

unofficial driver
Swift

Server-side scripts

Stored procedures

in Natural

JavaScript

Triggers

yes

in MongoDB Atlas only

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

Sharding

Partitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

yes, via HDFS, S3 or other storage engines

Source-replica replication

Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

ACID

ACID at container level

Multi-document ACID Transactions with snapshot isolation

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional, enabled by default

yes

In-memory capabilities

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

yes

In-memory storage engine introduced with MongoDB version 3.2

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 rights for users can be defined per database

Access rights for users and roles

Users with fine-grained authorization concept

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

MongoDB provides an integrated suite of cloud database and data services to accelerate...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Built around the flexible document data model and unified API, MongoDB is a developer...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

ADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more

Market metrics

GitHub trending repository
» more

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.