DBMS > Alibaba Cloud Table Store vs. EsgynDB vs. Galaxybase vs. Google Cloud Bigtable

System Properties Comparison Alibaba Cloud Table Store vs. EsgynDB vs. Galaxybase vs. Google Cloud Bigtable

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Scalable, ACID-compliant native distributed parallel graph platform

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

Wide column store

Relational DBMS

Graph DBMS

Key-value store
Wide column store

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#383	Overall
	#39	Graph DBMS

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

Website

www.alibabacloud.com/product/table-store

www.esgyn.cn

galaxybase.com

cloud.google.com/bigtable

Technical documentation

www.alibabacloud.com/help/en/tablestore

cloud.google.com/bigtable/docs

Developer

Alibaba

Esgyn

Chuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司

Google

Initial release

2016

2015

2017

2015

Current release

Nov 20, November 2021

License

Commercial or Open Source

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

C++, Java

C and Java

Server operating systems

hosted

Linux

hosted

Data scheme

schema-free

yes

Strong typed schema

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

SQL

Support of SQL

yes

APIs and other access methods

HTTP API

ADO.NET
JDBC
ODBC

Browser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API

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

Supported programming languages

Java
Python

All languages supporting JDBC/ODBC/ADO.Net

Go
Java
Python

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

Server-side scripts

Stored procedures

Java Stored Procedures

user defined procedures and functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

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

Multi-source replication between multi datacenters

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

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

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

Atomic single-row operations

ACID

Atomic single-row operations

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.

yes

User concepts

Access control

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

Role-based access control

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

Apache Software Foundation Announces New Top-Level Project Apache Paimon
19 April 2024, Datanami

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

25 Best Cloud Service Providers (Public and Private) in 2024
4 June 2023, CybersecurityNews

Top data analytics tools comparison: Alibaba Cloud, AWS, Azure, Google Cloud, IBM
5 December 2019, Wire19

Apache Paimon Elevates to Top-Level Project, Revolutionizing Data Lake Architectures
18 April 2024, MyChesCo

provided by Google News

做国产图数据库，「创邻科技」将拓展国际市场| 新科技创业
5 April 2023, 36kr

创邻科技，位居IDC MarketScape中国图数据库市场领导者类别
13 September 2023, blog.csdn.net

provided by Google News

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

What is Google Bigtable? | Definition from TechTarget
1 March 2022, TechTarget

Google announces Axion, its first Arm-based CPU for data centers
9 April 2024, Yahoo Movies Canada

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

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

provided by Google News

Share this page