DBMS > EXASOL vs. KeyDB vs. Netezza vs. RethinkDB vs. Snowflake

System Properties Comparison EXASOL vs. KeyDB vs. Netezza vs. RethinkDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

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

Data warehouse and analytics appliance part of IBM PureSystems

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

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

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.exasol.com

github.com/Snapchat/KeyDB
keydb.dev

www.ibm.com/products/netezza

rethinkdb.com

www.snowflake.com

Technical documentation

www.exasol.com/resources

docs.keydb.dev

rethinkdb.com/docs

docs.snowflake.net/manuals/index.html

Developer

Exasol

EQ Alpha Technology Ltd.

IBM

The Linux Foundation

since July 2017

Snowflake Computing Inc.

Initial release

2000

2019

2000

2009

2014

Current release

2.4.1, August 2020

License

Commercial or Open Source

commercial

Open Source

BSD-3

commercial

Open Source

Apache Version 2

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

Linux

included in appliance

Linux
OS X
Windows

hosted

Data scheme

yes

schema-free

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

string, binary, float, bool, date, geometry

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

yes

SQL

Support of SQL

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

Java
Lua
Python
R

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

C
C++
Fortran
Java
Lua
Perl
Python
R

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

Lua

yes

user defined functions

Triggers

yes

Client-side triggers through changefeeds

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate 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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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

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

simple password-based access control and ACL

Users with fine-grained authorization concept

yes

users and table-level permissions

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

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