DBMS > Google BigQuery vs. Manticore Search vs. OpenQM vs. Teradata Aster

System Properties Comparison Google BigQuery vs. Manticore Search vs. OpenQM vs. Teradata Aster

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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 with append-only tables

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Platform for big data analytics on multistructured data sources and types

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Website

cloud.google.com/bigquery

manticoresearch.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

cloud.google.com/bigquery/docs

manual.manticoresearch.com

Developer

Google

Manticore Software

Rocket Software, originally Martin Phillips

Teradata

Initial release

2010

2017

1993

2005

Current release

6.0, February 2023

3.4-12

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

GPLv2, extended commercial license available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

yes

Fixed schema

yes

with some exceptions

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

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

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP/JSON API

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

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

.Net
Basic
C
Java
Objective C
PHP
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

user defined functions

in JavaScript

user defined functions

yes

R packages

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Since BigQuery is designed for querying data

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.

User concepts

Access control

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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