DBMS > Amazon Redshift vs. Axibase vs. Informix vs. SWC-DB vs. Vertica

System Properties Comparison Amazon Redshift vs. Axibase vs. Informix vs. SWC-DB vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

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

A high performance, scalable Wide Column DBMS

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Relational DBMS

Time Series DBMS

Relational DBMS

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

Wide column store

Relational DBMS

Column oriented

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Time Series DBMS

Spatial DBMS
Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

aws.amazon.com/redshift

axibase.com/docs/atsd/finance

www.ibm.com/products/informix

github.com/kashirin-alex/swc-db
www.swcdb.org

www.vertica.com

Technical documentation

docs.aws.amazon.com/redshift

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

vertica.com/documentation

Developer

Amazon (based on PostgreSQL)

Axibase Corporation

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.

Alex Kashirin

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2012

2013

1984

2020

2005

Current release

15585

14.10.FC5, November 2020

0.5, April 2021

12.0.3, January 2023

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

free developer edition available

Open Source

GPL V3

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

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

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

Data scheme

yes

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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.

Secondary indexes

restricted

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

SQL-like query language

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
JSON API

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

Proprietary protocol
Thrift

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

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

C++

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

Server-side scripts

Stored procedures

user defined functions

in Python

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication
Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

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

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

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

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

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Key customers

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Licensing and pricing models

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