DBMS > Adabas vs. dBASE vs. Google Cloud Bigtable vs. MongoDB vs. TypeDB

System Properties Comparison Adabas vs. dBASE vs. Google Cloud Bigtable vs. MongoDB vs. TypeDB

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

dBase was one of the first databases with a development environment on PC's. Its latest version dBase V is still sold as dBase classic, which needs a DOS Emulation. The up-to-date product is dBase plus.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Multivalue DBMS

Relational DBMS

Key-value store
Wide column store

Document store

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

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	2.79
Rank	#102	Overall
	#2	Multivalue DBMS

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	421.08
Rank	#5	Overall
	#1	Document stores

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

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

www.dbase.com

cloud.google.com/bigtable

www.mongodb.com

typedb.com

Technical documentation

www.dbase.com/support/knowledgebase

cloud.google.com/bigtable/docs

www.mongodb.com/docs/manual

typedb.com/docs

Developer

Software AG

Asthon Tate

Google

MongoDB, Inc

Vaticle

Initial release

1971

1979

2015

2009

2016

Current release

dBASE 2019, 2019

6.0.7, June 2023

2.26.3, January 2024

License

Commercial or Open Source

commercial

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

GPL Version 3, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

MongoDB available as DBaaS (MongoDB Atlas)

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Implementation language

C++

Java

Server operating systems

BS2000
Linux
Unix
Windows
z/OS
z/VSE

DOS

dBase Classic
Windows

dBase Pro

hosted

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

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.

yes

Typing

predefined data types such as float or date

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

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

none

The IDE can access other DBMS or ODBC-sources.

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

GraphQL
HTTP REST
Prisma
proprietary protocol using JSON

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

Natural

dBase proprietary IDE

C#
C++
Go
Java
JavaScript (Node.js)
Python

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

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

in Natural

The IDE can access stored procedures in other database systems.

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

none

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

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with add-on product Event Replicator

none

Internal replication in Colossus, and regional replication between two clusters in different zones

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

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

can be individually decided for each read operation
Immediate Consistency

default behaviour

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

substituted by the relationship feature

Transaction concepts

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

ACID

not for dBase internal data, but IDE does support transactions when accessing external DBMS

Atomic single-row operations

Multi-document ACID Transactions with snapshot isolation

ACID

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)

Access rights for users and roles

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

MongoDB provides an integrated suite of cloud database and data services to accelerate...
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TypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
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Competitive advantages

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

TypeDB provides a new level of expressivity, extensibility, interoperability, and...
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Typical application scenarios

AI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
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Life sciences : TypeDB makes working with biological data much easier and accelerates...
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Key customers

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

Market metrics

Hundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
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Licensing and pricing models

MongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
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Apache f or language drivers, and AGPL and Commercial for the database server. The...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.