DBMS > Google Cloud Datastore vs. Microsoft Azure Table Storage vs. SAP HANA vs. TiDB

System Properties Comparison Google Cloud Datastore vs. Microsoft Azure Table Storage vs. SAP HANA vs. TiDB

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Editorial information provided by DB-Engines

Name

Description

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A Wide Column Store for rapid development using massive semi-structured datasets

In-memory, column based data store. Available as appliance or cloud service

TiDB is an open source distributed SQL database that supports Hybrid Transactional/Analytical Processing (HTAP) workloads. It is MySQL compatible and features horizontal scalability, strong consistency, and high availability.

Primary database model

Document store

Wide column store

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store

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

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	4.48
Rank	#75	Overall
	#6	Wide column stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Score	4.66
Rank	#70	Overall
	#38	Relational DBMS

Website

cloud.google.com/datastore

azure.microsoft.com/en-us/services/storage/tables

www.sap.com/products/hana.html

pingcap.com

Technical documentation

cloud.google.com/datastore/docs

help.sap.com/hana

docs.pingcap.com/tidb/stable

Developer

Google

Microsoft

SAP

PingCAP, Inc.

Initial release

2008

2012

2010

2016

Current release

2.0 SPS07 (April 4, 2023), April 2023

8.0.0, March 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

TiDB Cloud: Fully-managed TiDB Service. Bring everything great about TiDB to the cloud.

Implementation language

Go, Rust

Server operating systems

hosted

Appliance or cloud-service

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes, details here

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

SQL-like query language (GQL)

yes

APIs and other access methods

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC

GORM
JDBC
ODBC
Proprietary protocol
SQLAlchemy

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

using Google App Engine

SQLScript, R

Triggers

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

horizontal partitioning (by key range)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using Paxos

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

yes

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

with TiSpark Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

full support since version 6.6

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

optimistic locking

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.

yes

User concepts

Access control

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

Access rights based on private key authentication or shared access signatures

yes

Fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

TiDB is an advanced open-source, distributed SQL database for modern application...
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Competitive advantages

- HORIZONTAL SCALING : TiDB grants total transparency into your data workloads without...
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Typical application scenarios

TiDB is ideal for transactional applications that require extreme scalability and...
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Key customers

Block, Pinterest, Catalyst, Bolt, Flipkart, Capcom, Shopee (E-commerce), JD Cloud...
» more

Market metrics

34K+ GitHub stars 5K+ members in TiDB Community Slack 1K+ community contributors...
» more

Licensing and pricing models

TiDB Community : Free open source software (Apache 2.0) TiDB Self-Hosted : Enterprise...
» more

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