DBMS > Apache Kylin vs. GridGain vs. Machbase Neo vs. Transbase

System Properties Comparison Apache Kylin vs. GridGain vs. Machbase Neo vs. Transbase

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Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

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

TimeSeries DBMS for AIoT and BigData

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

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

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

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

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

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

kylin.apache.org

www.gridgain.com

machbase.com

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

Technical documentation

kylin.apache.org/docs

www.gridgain.com/docs/index.html

machbase.com/dbms

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

Developer

Apache Software Foundation, originally contributed from eBay Inc

GridGain Systems, Inc.

Machbase

Transaction Software GmbH

Initial release

2015

2007

2013

1987

Current release

3.1.0, July 2020

GridGain 8.5.1

V8.0, August 2023

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free test version available

commercial

free development license

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, C++, .Net

C and C++

Server operating systems

Linux

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

Typing

predefined data types such as float or date

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 SQL for queries (using Apache Calcite)

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

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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)

yes

Triggers

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

volatile and lookup table

User concepts

Access control

Security Hooks for custom implementations

simple password-based access control

fine grained access rights according to SQL-standard

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More resources

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