DBMS > Alibaba Cloud MaxCompute vs. GridGain vs. Heroic vs. Transwarp StellarDB

System Properties Comparison Alibaba Cloud MaxCompute vs. GridGain vs. Heroic vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

MaxCompute (previously known as ODPS) is a general purpose, fully managed, multi-tenancy data processing platform for large-scale data warehousing

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Relational DBMS

a graph-processing framework is available with the graphs being stored in tables

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

Graph DBMS

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

Score	0.85
Rank	#203	Overall
	#96	Relational DBMS

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

Score	0.13
Rank	#335	Overall
	#29	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Graph DBMS

Website

www.alibabacloud.com/product/maxcompute

www.gridgain.com

github.com/spotify/heroic

www.transwarp.cn/en/product/stellardb

Technical documentation

www.alibabacloud.com/help/en/maxcompute

www.gridgain.com/docs/index.html

spotify.github.io/heroic

Developer

Alibaba

GridGain Systems, Inc.

Spotify

Transwarp

Initial release

2016

2007

2014

Current release

GridGain 8.5.1

License

Commercial or Open Source

commercial

commercial, open source

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

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

Java

Server operating systems

hosted

Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

schema-free

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

via Elasticsearch

SQL

Support of SQL

SQL-like query language

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

SQL-like query language

APIs and other access methods

Fluentd
Flume
MaxCompute Console

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

HQL (Heroic Query Language, a JSON-based language)
HTTP API

OpenCypher

Supported programming languages

Java

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Java

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

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes (replicated cache)

yes

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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

User concepts

Access control

Access rights for users and roles

Role-based access control
Security Hooks for custom implementations

yes

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