DBMS > Amazon Redshift vs. Hive vs. Informix vs. Manticore Search vs. Teradata Aster

System Properties Comparison Amazon Redshift vs. Hive vs. Informix vs. Manticore Search vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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

Multi-storage database for search, including full-text search.

Platform for big data analytics on multistructured data sources and types

Primary database model

Relational DBMS

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

Search engine

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Time Series DBMS

using the Manticore Columnar Library

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Website

aws.amazon.com/redshift

hive.apache.org

www.ibm.com/products/informix

manticoresearch.com

Technical documentation

docs.aws.amazon.com/redshift

cwiki.apache.org/confluence/display/Hive/Home

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

manual.manticoresearch.com

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

initially developed by Facebook

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.

Manticore Software

Teradata

Initial release

2012

1984

2017

2005

Current release

3.1.3, April 2022

14.10.FC5, November 2020

6.0, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

free developer edition available

Open Source

GPL version 2

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

All OS with a Java VM

AIX
HP-UX
Linux
macOS
Solaris
Windows

FreeBSD
Linux
macOS
Windows

Linux

Data scheme

yes

Fixed schema

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

yes

in Aster File Store

Secondary indexes

restricted

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC

JDBC
ODBC
Thrift

JDBC
JSON API

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

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

C++
Java
PHP
Python

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

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

yes

user defined functions

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Multi-source replication
Source-replica replication

Synchronous replication based on Galera library

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Manticore index.

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

Access rights for users, groups and roles

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

fine grained access rights according to SQL-standard

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