DBMS > Alibaba Cloud MaxCompute vs. Badger vs. EJDB vs. Google Cloud Bigtable

System Properties Comparison Alibaba Cloud MaxCompute vs. Badger vs. EJDB vs. Google Cloud Bigtable

Please select another system to include it in the comparison.

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Primary database model

Relational DBMS

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

Key-value store

Document store

Key-value store
Wide column store

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	0.27
Rank	#297	Overall
	#44	Document stores

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Website

www.alibabacloud.com/product/maxcompute

github.com/dgraph-io/badger

github.com/Softmotions/ejdb

cloud.google.com/bigtable

Technical documentation

www.alibabacloud.com/help/en/maxcompute

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

github.com/Softmotions/ejdb/blob/master/README.md

cloud.google.com/bigtable/docs

Developer

Alibaba

DGraph Labs

Softmotions

Google

Initial release

2016

2017

2012

2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPLv2

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

Server operating systems

hosted

BSD
Linux
OS X
Solaris
Windows

server-less

hosted

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

Fluentd
Flume
MaxCompute Console

in-process shared library

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

Supported programming languages

Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

in Java

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Internal replication in Colossus, and regional replication between two clusters in different zones

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Atomic single-row operations

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

More information provided by the system vendor

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

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Alibaba Cloud To Launch Big Data Service in Europe
15 June 2017, Alizila

Streaming Data Services Comparison: Alibaba Cloud, AWS, Azure, Google Cloud, IBM Cloud
20 January 2020, Wire19

How Big Data Platform Helped Power Last Year's Double 11
3 March 2020, DataDrivenInvestor

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

Alibaba VP Yangqing Jia to Quit and Start Own AI Business
21 March 2023, Pandaily

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google expands BigQuery with Gemini, brings vector support to cloud databases
29 February 2024, VentureBeat

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

provided by Google News

Share this page