DBMS > JaguarDB vs. KeyDB vs. Lovefield vs. Netezza vs. Snowflake

System Properties Comparison JaguarDB vs. KeyDB vs. Lovefield vs. Netezza vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Embeddable relational database for web apps written in pure JavaScript

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

Key-value store
Vector DBMS

Key-value store

Relational DBMS

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

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Score	0.80
Rank	#219	Overall
	#31	Key-value stores

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	10.18
Rank	#46	Overall
	#29	Relational DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Website

www.jaguardb.com

github.com/Snapchat/KeyDB
keydb.dev

google.github.io/lovefield

www.ibm.com/products/netezza

www.snowflake.com

Technical documentation

www.jaguardb.com/support.html

docs.keydb.dev

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.snowflake.net/manuals/index.html

Developer

DataJaguar, Inc.

EQ Alpha Technology Ltd.

Google

IBM

Snowflake Computing Inc.

Initial release

2015

2019

2014

2000

2014

Current release

3.3 July 2023

2.1.12, February 2017

License

Commercial or Open Source

Open Source

GPL V3.0

Open Source

BSD-3

Open Source

Apache 2.0

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++

the server part. Clients available in other languages

C++

JavaScript

Server operating systems

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux

included in appliance

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

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
ODBC
OLE DB

CLI Client
JDBC
ODBC

Supported programming languages

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

C
C++
Fortran
Java
Lua
Perl
Python
R

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

yes

user defined functions

Triggers

Using read-only observers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

none

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

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

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, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

rights management via user accounts

simple password-based access control and ACL

Users with fine-grained authorization concept

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

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