DBMS > DuckDB vs. Google Cloud Bigtable vs. OpenQM vs. searchxml

System Properties Comparison DuckDB vs. Google Cloud Bigtable vs. OpenQM vs. searchxml

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Editorial information provided by DB-Engines

Name

Description

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS

Key-value store
Wide column store

Multivalue DBMS

Native XML DBMS
Search engine

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

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

duckdb.org

cloud.google.com/bigtable

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

www.searchxml.net/category/products

Technical documentation

duckdb.org/docs

cloud.google.com/bigtable/docs

www.searchxml.net/support/handouts

Developer

Google

Rocket Software, originally Martin Phillips

informationpartners gmbh

Initial release

2018

2015

1993

2015

Current release

0.10, February 2024

3.4-12

1.0

License

Commercial or Open Source

Open Source

MIT License

commercial

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

server-less

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Windows

Data scheme

yes

schema-free

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

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

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

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

.Net
Basic
C
Java
Objective C
PHP
Python

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic single-row operations

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

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

Domain, group and role-based access control at the document level and for application services

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More resources

Recent citations in the news

DuckDB: In-Process Python Analytics for Not-Quite-Big Data
31 May 2024, The New Stack

MotherDuck launches its DuckDB-based cloud analytics platform
30 May 2024, MSN

DuckDB Walks to the Beat of Its Own Analytics Drum
5 March 2024, Datanami

DuckDB: The tiny but powerful analytics database
15 May 2024, InfoWorld

My First Billion (of Rows) in DuckDB | by João Pedro | May, 2024
1 May 2024, Towards Data Science

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

provided by Google News

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