DBMS > Drizzle vs. EXASOL vs. JaguarDB vs. KeyDB vs. Snowflake

System Properties Comparison Drizzle vs. EXASOL vs. JaguarDB vs. KeyDB vs. Snowflake

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.

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Performant, highly scalable DBMS for AI and IoT applications

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Relational DBMS

Key-value store
Vector DBMS

Key-value store

Relational DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.exasol.com

www.jaguardb.com

github.com/Snapchat/KeyDB
keydb.dev

www.snowflake.com

Technical documentation

www.exasol.com/resources

www.jaguardb.com/support.html

docs.keydb.dev

docs.snowflake.net/manuals/index.html

Developer

Drizzle project, originally started by Brian Aker

Exasol

DataJaguar, Inc.

EQ Alpha Technology Ltd.

Snowflake Computing Inc.

Initial release

2008

2000

2015

2019

2014

Current release

7.2.4, September 2012

3.3 July 2023

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

GPL V3.0

Open Source

BSD-3

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

C++

the server part. Clients available in other languages

C++

Server operating systems

FreeBSD
Linux
OS X

Linux

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

SQL

Support of SQL

yes

with proprietary extensions

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

CLI Client
JDBC
ODBC

Supported programming languages

C
C++
Java
PHP

Java
Lua
Python
R

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Lua

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles according to SQL-standard

rights management via user accounts

simple password-based access control and ACL

Users with fine-grained authorization concept, user roles and pluggable authentication

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