DBMS > Alibaba Cloud MaxCompute vs. Altibase vs. DataFS vs. Splice Machine vs. TimescaleDB

System Properties Comparison Alibaba Cloud MaxCompute vs. Altibase vs. DataFS vs. Splice Machine vs. TimescaleDB

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

An enterprise grade, high-performance RDBMS

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Relational DBMS

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

Secondary database models

Graph DBMS

Relational DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	1.07
Rank	#186	Overall
	#87	Relational DBMS

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

www.alibabacloud.com/product/maxcompute

Technical documentation

www.alibabacloud.com/help/en/maxcompute

github.com/ALTIBASE/Documents/tree/master/Manuals

dev.mobiland.com/Overview.xsp

splicemachine.com/how-it-works

docs.timescale.com

Developer

Alibaba

Altibase

Mobiland AG

Splice Machine

Timescale

Initial release

2016

1999

2018

2014

2017

Current release

v7.3, 2023, August 2023

1.1.263, October 2022

3.1, March 2021

2.15.0, May 2024

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

Open Source

AGPL 3.0, commercial license 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

AIX
HP-UX
Linux

Windows

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL-like query language

ANSI SQL-92

yes

full PostgreSQL SQL syntax

APIs and other access methods

Fluentd
Flume
MaxCompute Console

JDBC
ODBC
Proprietary protocol

.NET Client API
Proprietary client DLL
WinRT client

JDBC
Native Spark Datasource
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java

C
C++
Java

.Net
C
C#
C++
VB.Net

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Java

stored procedures and stored functions

yes

Java

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

no, except callback-events from server when changes happened

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Proprietary Sharding system

Shared Nothhing Auto-Sharding, Columnar Partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Multi-source replication
Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Windows-Profile

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

More information provided by the system vendor

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