DBMS > Amazon Redshift vs. Axibase vs. GeoMesa vs. Informix vs. Tigris

System Properties Comparison Amazon Redshift vs. Axibase vs. GeoMesa vs. Informix vs. Tigris

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

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 horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

Primary database model

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

Document store
Key-value store
Search engine
Time Series DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	0.09
Rank	#363	Overall
	#49	Document stores
	#54	Key-value stores
	#22	Search engines
	#38	Time Series DBMS

Website

aws.amazon.com/redshift

axibase.com/docs/atsd/finance

www.geomesa.org

www.ibm.com/products/informix

www.tigrisdata.com

Technical documentation

docs.aws.amazon.com/redshift

www.geomesa.org/documentation/stable/user/index.html

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

www.tigrisdata.com/docs

Developer

Amazon (based on PostgreSQL)

Axibase Corporation

CCRi and others

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.

Tigris Data, Inc.

Initial release

2012

2013

2014

1984

2022

Current release

15585

5.0.0, May 2024

14.10.FC5, November 2020

License

Commercial or Open Source

commercial

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

Open Source

Apache License 2.0

commercial

free developer edition available

Open Source

Apache Version 2.0

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

Scala

C, C++ and Java

Server operating systems

hosted

Linux

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

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

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like query language

yes

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

CLI Client
gRPC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

Go
Java
PHP
Python
R
Ruby

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

Go
Java
JavaScript (Node.js)

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

depending on storage layer

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

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

yes, using FoundationDB

In-memory capabilities

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

yes

depending on storage layer

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

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

Access rights for users and roles

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