DBMS > Google Cloud Bigtable vs. Manticore Search vs. OpenQM vs. Postgres-XL

System Properties Comparison Google Cloud Bigtable vs. Manticore Search vs. OpenQM vs. Postgres-XL

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Editorial information provided by DB-Engines

Name

Description

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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

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

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Key-value store
Wide column store

Search engine

Multivalue DBMS

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Document store
Spatial DBMS

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

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

cloud.google.com/bigtable

manticoresearch.com

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

www.postgres-xl.org

Technical documentation

cloud.google.com/bigtable/docs

manual.manticoresearch.com

www.postgres-xl.org/documentation

Developer

Google

Manticore Software

Rocket Software, originally Martin Phillips

Initial release

2015

2017

1993

2014

since 2012, originally named StormDB

Current release

6.0, February 2023

3.4-12

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

GPL version 2

Open Source

GPLv2, extended commercial license available

Open Source

Mozilla public license

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

C++

Server operating systems

hosted

FreeBSD
Linux
macOS
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux
macOS

Data scheme

schema-free

Fixed schema

yes

with some exceptions

yes

Typing

predefined data types such as float or date

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

XML type, but no XML query functionality

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like query language

yes

distributed, parallel query execution

APIs and other access methods

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

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

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

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

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

Synchronous replication based on Galera library

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

MVCC

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 rights for users, groups and roles based on Google Cloud Identity and 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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