DBMS > Alibaba Cloud MaxCompute vs. GridDB vs. Hazelcast vs. JSqlDb vs. Newts

System Properties Comparison Alibaba Cloud MaxCompute vs. GridDB vs. Hazelcast vs. JSqlDb vs. Newts

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Scalable in-memory time series database optimized for IoT and Big Data

A widely adopted in-memory data grid

JavaScript Query Language Database, stores JavaScript objects and primitives

Time Series DBMS based on Cassandra

Primary database model

Relational DBMS

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

Time Series DBMS

Key-value store

Document store
Object oriented DBMS

Time Series DBMS

Secondary database models

Key-value store
Relational DBMS

Document store

JSON support with IMDG 3.12

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

Score	0.84
Rank	#209	Overall
	#98	Relational DBMS

Score	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

www.alibabacloud.com/product/maxcompute

griddb.net

hazelcast.com

jsqldb.org (offline)

opennms.github.io/newts

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.griddb.net

hazelcast.org/imdg/docs

github.com/OpenNMS/newts/wiki

Developer

Alibaba

Toshiba Corporation

Hazelcast

Konrad von Backstrom

OpenNMS Group

Initial release

2016

2013

2008

2018

2014

Current release

5.1, August 2022

5.3.6, November 2023

0.8, December 2018

License

Commercial or Open Source

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

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++

Java

Server operating systems

hosted

Linux

All OS with a Java VM

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

the object must implement a serialization strategy

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JCache
JPA
Memcached protocol
RESTful HTTP API

HTTP REST
Java API

Supported programming languages

Java

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

JavaScript

Java

Server-side scripts

Stored procedures

user defined functions

in Java

yes

Event Listeners, Executor Services

functions in JavaScript

Triggers

yes

Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

yes

Replicated Map

none

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

Transaction concepts

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

ACID at container level

one or two-phase-commit; repeatable reads; read commited

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

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

Access rights for users can be defined per database

Role-based access control

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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.

Related products and services

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