DBMS > Alibaba Cloud MaxCompute vs. Badger vs. Brytlyt vs. Microsoft Azure Cosmos DB vs. Trafodion

System Properties Comparison Alibaba Cloud MaxCompute vs. Badger vs. Brytlyt vs. Microsoft Azure Cosmos DB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. 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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Globally distributed, horizontally scalable, multi-model database service

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

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

Key-value store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

www.alibabacloud.com/product/maxcompute

github.com/dgraph-io/badger

brytlyt.io

azure.microsoft.com/services/cosmos-db

trafodion.apache.org

Technical documentation

www.alibabacloud.com/help/en/maxcompute

godoc.org/github.com/dgraph-io/badger

docs.brytlyt.io

learn.microsoft.com/azure/cosmos-db

trafodion.apache.org/documentation.html

Developer

Alibaba

DGraph Labs

Brytlyt

Microsoft

Apache Software Foundation, originally developed by HP

Initial release

2016

2017

2016

2014

Current release

5.0, August 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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, C++ and CUDA

C++, Java

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

hosted

Linux

Data scheme

yes

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

yes

APIs and other access methods

Fluentd
Flume
MaxCompute Console

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

ADO.NET
JDBC
ODBC

Supported programming languages

Java

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

in Java

user defined functions

in PL/pgSQL

JavaScript

Java Stored Procedures

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Source-replica replication

yes

Implicit feature of the cloud service

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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.

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

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