DBMS > Amazon Redshift vs. Apache IoTDB vs. Datomic vs. dBASE vs. Elasticsearch

System Properties Comparison Amazon Redshift vs. Apache IoTDB vs. Datomic vs. dBASE vs. Elasticsearch

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Primary database model

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	10.34
Rank	#44	Overall
	#28	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Website

aws.amazon.com/redshift

iotdb.apache.org

www.datomic.com

www.dbase.com

www.elastic.co/elasticsearch

Technical documentation

docs.aws.amazon.com/redshift

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.datomic.com

www.dbase.com/support/knowledgebase

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Cognitect

Asthon Tate

Elastic

Initial release

2012

2018

2012

1979

2010

Current release

1.1.0, April 2023

1.0.6735, June 2023

dBASE 2019, 2019

8.6, January 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

limited edition free

commercial

Open Source

Elastic License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, Clojure

Java

Server operating systems

hosted

All OS with a Java VM (>= 1.8)

All OS with a Java VM

DOS

dBase Classic
Windows

dBase Pro

All OS with a Java VM

Data scheme

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

restricted

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

APIs and other access methods

JDBC
ODBC

JDBC
Native API

RESTful HTTP API

none

The IDE can access other DBMS or ODBC-sources.

Java API
RESTful HTTP/JSON API

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Go
Java
Python
Scala

Clojure
Java

dBase proprietary IDE

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Transaction Functions

The IDE can access stored procedures in other database systems.

yes

Triggers

yes

By using transaction functions

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

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 methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

none

But extensive use of caching in the application peers

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Memcached and Redis integration

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

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