DBMS > Drizzle vs. IBM Cloudant vs. Spark SQL vs. SurrealDB

System Properties Comparison Drizzle vs. IBM Cloudant vs. Spark SQL vs. SurrealDB

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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.

Database as a Service offering based on Apache CouchDB

Spark SQL is a component on top of 'Spark Core' for structured data processing

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Document store
Graph DBMS

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

Score	2.75
Rank	#104	Overall
	#19	Document stores

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

www.ibm.com/products/cloudant

spark.apache.org/sql

surrealdb.com

Technical documentation

cloud.ibm.com/docs/Cloudant

spark.apache.org/docs/latest/sql-programming-guide.html

surrealdb.com/docs

Developer

Drizzle project, originally started by Brian Aker

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Apache Software Foundation

SurrealDB Ltd

Initial release

2008

2010

2014

2022

Current release

7.2.4, September 2012

3.5.0 ( 2.13), September 2023

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

Apache 2.0

Open Source

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++

Erlang

Scala

Rust

Server operating systems

FreeBSD
Linux
OS X

hosted

Linux
OS X
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC

RESTful HTTP/JSON API

JDBC
ODBC

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

C
C++
Java
PHP

C#
Java
JavaScript
Objective-C
PHP
Ruby

Java
Python
R
Scala

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

View functions (Map-Reduce) in JavaScript

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

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.

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users can be defined per database

yes, based on authentication and database rules

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

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1 July 2013, Matthias Gelbmann

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