DBMS > Google Cloud Bigtable vs. OushuDB vs. TDSQL for MySQL vs. TempoIQ

System Properties Comparison Google Cloud Bigtable vs. OushuDB vs. TDSQL for MySQL vs. TempoIQ

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

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

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

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

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

Score	0.04
Rank	#363	Overall
	#154	Relational DBMS

Score	0.85
Rank	#205	Overall
	#95	Relational DBMS

Website

cloud.google.com/bigtable

www.oushu.com/product/oushuDB

www.tencentcloud.com/products/dcdb

tempoiq.com (offline)

Technical documentation

cloud.google.com/bigtable/docs

www.oushu.com/documentation

www.tencentcloud.com/document/product/1042

Developer

Google

Oushu

Tencent

TempoIQ

Initial release

2015

2013

2012

Current release

4.0.1, August 2020

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.

Server operating systems

hosted

Linux

hosted

Data scheme

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

SQL

Support of SQL

Full-featured ANSI SQL support

yes

APIs and other access methods

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

JDBC
ODBC

HTTP API

Supported programming languages

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

C
C++

C
C#
C++
Java
PHP
Python
Ruby

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

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

Kerberos, SSL and role based access

Users with fine-grained authorization concept

simple authentication-based access control

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