DBMS > Drizzle vs. Google Cloud Bigtable vs. TerminusDB

System Properties Comparison Drizzle vs. Google Cloud Bigtable vs. TerminusDB

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Key-value store
Wide column store

Graph DBMS

Secondary database models

Document store
RDF store

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

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Website

cloud.google.com/bigtable

terminusdb.com

Technical documentation

cloud.google.com/bigtable/docs

terminusdb.github.io/terminusdb/#

Developer

Drizzle project, originally started by Brian Aker

Google

DataChemist Ltd.

Initial release

2008

2015

2018

Current release

7.2.4, September 2012

11.0.0, January 2023

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

GPL V3

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++

Prolog, Rust

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language (WOQL)

APIs and other access methods

JDBC

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

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C++
Java
PHP

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

JavaScript
Python

Server-side scripts

Stored procedures

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

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

Journaling Streams

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)

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Role-based access control

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More resources

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