DBMS > Amazon Redshift vs. Apache Druid vs. Informix vs. searchxml vs. TDSQL for MySQL

System Properties Comparison Amazon Redshift vs. Apache Druid vs. Informix vs. searchxml vs. TDSQL for MySQL

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

DBMS for structured and unstructured content wrapped with an application server

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Primary database model

Relational DBMS

Relational DBMS
Time Series DBMS

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Native XML DBMS
Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Document store
Spatial DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.85
Rank	#207	Overall
	#97	Relational DBMS

Website

aws.amazon.com/redshift

druid.apache.org

www.ibm.com/products/informix

www.searchxml.net/category/products

www.tencentcloud.com/products/dcdb

Technical documentation

docs.aws.amazon.com/redshift

druid.apache.org/docs/latest/design

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

www.searchxml.net/support/handouts

www.tencentcloud.com/document/product/1042

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation and contributors

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

informationpartners gmbh

Tencent

Initial release

2012

1984

2015

2013

Current release

29.0.1, April 2024

14.10.FC5, November 2020

1.0

License

Commercial or Open Source

commercial

Open Source

Apache license v2

commercial

free developer edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C, C++ and Java

C++

Server operating systems

hosted

Linux
OS X
Unix

AIX
HP-UX
Linux
macOS
Solaris
Windows

Windows

hosted

Data scheme

yes

schema-less columns are supported

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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

SQL for querying

yes

APIs and other access methods

JDBC
ODBC

JDBC
RESTful HTTP/JSON API

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

RESTful HTTP API
WebDAV
XQuery
XSLT

JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C++

most other programming languages supported via APIs

C
C#
C++
Java
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

yes

on the application server

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, via HDFS, S3 or other storage engines

Multi-source replication
Source-replica replication

yes

sychronisation to multiple collections

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

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

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Users with fine-grained authentication, authorization, and auditing controls

Domain, group and role-based access control at the document level and for application services

Users with fine-grained authorization concept

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