DBMS > GridGain vs. NCache vs. Snowflake vs. Tibero vs. Transbase

System Properties Comparison GridGain vs. NCache vs. Snowflake vs. Tibero vs. Transbase

Editorial information provided by DB-Engines

Name

Description

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

Open-Source and Enterprise in-memory Key-Value Store

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

A secure RDBMS, designed for easy portability from Oracle

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

Primary database model

Key-value store
Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

www.gridgain.com

www.alachisoft.com/ncache

www.snowflake.com

us.tmaxsoft.com/products/tibero

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

Technical documentation

www.gridgain.com/docs/index.html

www.alachisoft.com/resources/docs

docs.snowflake.net/manuals/index.html

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

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

Developer

GridGain Systems, Inc.

Alachisoft

Snowflake Computing Inc.

TmaxSoft

Transaction Software GmbH

Initial release

2007

2005

2014

2003

1987

Current release

GridGain 8.5.1

5.3.3, April 2024

6, April 2015

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

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

C#, .NET, .NET Core, Java

C and Assembler

C and C++

Server operating systems

Linux
OS X
Solaris
Windows

Linux
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

SQL

Support of SQL

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

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

yes

APIs and other access methods

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

IDistributedCache
JCache
LINQ
Proprietary native API

CLI Client
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

JavaScript (Node.js)
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

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)

support for stored procedures with SQL-Server CLR

user defined functions

Persistent Stored Procedure (PSM)

yes

Triggers

yes (cache interceptors and events)

yes

Notifications

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes, with selectable consistency level

yes

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

ACID

yes

Concurrency

Support for concurrent manipulation of data

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.

yes

planned for next version

User concepts

Access control

Security Hooks for custom implementations

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

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

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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