DBMS > GridGain vs. KeyDB vs. Snowflake vs. SWC-DB vs. Transbase

System Properties Comparison GridGain vs. KeyDB vs. Snowflake vs. SWC-DB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

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

A high performance, scalable Wide Column DBMS

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Secondary database models

Time Series DBMS

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

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	0.63
Rank	#232	Overall
	#32	Key-value stores

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Score	0.05
Rank	#355	Overall
	#150	Relational DBMS

Website

www.gridgain.com

github.com/Snapchat/KeyDB
keydb.dev

www.snowflake.com

github.com/kashirin-alex/swc-db
www.swcdb.org

www.transaction.de/en/products/transbase.html

Technical documentation

www.gridgain.com/docs/index.html

docs.keydb.dev

docs.snowflake.net/manuals/index.html

www.transaction.de/en/products/transbase/features.html

Developer

GridGain Systems, Inc.

EQ Alpha Technology Ltd.

Snowflake Computing Inc.

Alex Kashirin

Transaction Software GmbH

Initial release

2007

2019

2014

2020

1987

Current release

GridGain 8.5.1

0.5, April 2021

Transbase 8.3, 2022

License

Commercial or Open Source

commercial, open source

Open Source

BSD-3

commercial

Open Source

GPL V3

commercial

free development license

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

Java, C++, .Net, Python, REST, SQL

C++

C and C++

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

Linux

hosted

Linux

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

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

schema-free

yes

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

ANSI-99 for query and DML statements, subset of DDL

yes

SQL-like query language

yes

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Proprietary protocol

RESP - REdis Serialization Protoco

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C#
C++
Java
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

C++

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

Lua

user defined functions

yes

Triggers

yes (cache interceptors and events)

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Multi-source replication
Source-replica replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

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

yes

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

Role-based access control
Security Hooks for custom implementations

simple password-based access control and ACL

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.