DBMS > Amazon Redshift vs. BigchainDB vs. Datomic vs. dBASE vs. Ignite

System Properties Comparison Amazon Redshift vs. BigchainDB vs. Datomic vs. dBASE vs. Ignite

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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.

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

Relational DBMS

Document store

Relational DBMS

Key-value store
Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	9.70
Rank	#44	Overall
	#28	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/redshift

bigchaindb.readthedocs.io/en/latest

docs.datomic.com

www.dbase.com/support/knowledgebase

apacheignite.readme.io/docs

Developer

Amazon (based on PostgreSQL)

Cognitect

Asthon Tate

Apache Software Foundation

Initial release

2012

2016

2012

1979

2015

Current release

1.0.7075, December 2023

dBASE 2019, 2019

Apache Ignite 2.6

License

Commercial or Open Source

commercial

Open Source

AGPL v3

commercial

limited edition free

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

Python

Java, Clojure

C++, Java, .Net

Server operating systems

hosted

Linux

All OS with a Java VM

DOS

dBase Classic
Windows

dBase Pro

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JDBC
ODBC

CLI Client
RESTful HTTP API

RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

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

Supported programming languages

All languages supporting JDBC/ODBC

Go
Haskell
Java
JavaScript
Python
Ruby

Clojure
Java

dBase proprietary IDE

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transaction Functions

The IDE can access stored procedures in other database systems.

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

Triggers

By using transaction functions

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

none

But extensive use of caching in the application peers

none

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

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

Security Hooks for custom implementations

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