DBMS > Alibaba Cloud MaxCompute vs. atoti vs. Badger vs. BigObject vs. PouchDB

System Properties Comparison Alibaba Cloud MaxCompute vs. atoti vs. Badger vs. BigObject vs. PouchDB

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 in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

Analytic DBMS for real-time computations and queries

JavaScript DBMS with an API inspired by CouchDB

Primary database model

Relational DBMS

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

Object oriented DBMS

Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Document store

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

Score	0.77
Rank	#214	Overall
	#98	Relational DBMS

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Website

www.alibabacloud.com/product/maxcompute

atoti.io

github.com/dgraph-io/badger

bigobject.io

pouchdb.com

Technical documentation

www.alibabacloud.com/help/en/maxcompute

docs.atoti.io

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

docs.bigobject.io

pouchdb.com/guides

Developer

Alibaba

ActiveViam

DGraph Labs

BigObject, Inc.

Apache Software Foundation

Initial release

2016

2017

2015

2012

Current release

7.1.1, June 2019

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache 2.0

commercial

free community edition available

Open Source

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

JavaScript

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

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.

Secondary indexes

yes

via views

SQL

Support of SQL

SQL-like query language

Multidimensional Expressions (MDX)

SQL-like DML and DDL statements

APIs and other access methods

Fluentd
Flume
MaxCompute Console

fluentd
ODBC
RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

Supported programming languages

Java

JavaScript

Server-side scripts

Stored procedures

user defined functions

in Java

Python

Lua

View functions in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Read/write lock on objects (tables, trees)

Durability

Support for making data persistent

yes

by using IndexedDB, WebSQL or LevelDB as backend

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

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More resources

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