DBMS > Alibaba Cloud Table Store vs. Google Cloud Bigtable vs. Microsoft SQL Server vs. NCache vs. VelocityDB

System Properties Comparison Alibaba Cloud Table Store vs. Google Cloud Bigtable vs. Microsoft SQL Server vs. NCache vs. VelocityDB

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

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

Microsofts flagship relational DBMS

Open-Source and Enterprise in-memory Key-Value Store

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Wide column store

Key-value store
Wide column store

Relational DBMS

Key-value store

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

www.alibabacloud.com/product/table-store

cloud.google.com/bigtable

www.microsoft.com/en-us/sql-server

www.alachisoft.com/ncache

velocitydb.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

cloud.google.com/bigtable/docs

learn.microsoft.com/en-US/sql/sql-server

www.alachisoft.com/resources/docs

velocitydb.com/UserGuide

Developer

Alibaba

Google

Microsoft

Alachisoft

VelocityDB Inc

Initial release

2016

2015

1989

2005

2011

Current release

SQL Server 2022, November 2022

5.3.3, April 2024

7.x

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Enterprise Edition available

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

C++

C#, .NET, .NET Core, Java

Server operating systems

hosted

Linux
Windows

Any that supports .NET

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

APIs and other access methods

HTTP API

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

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

IDistributedCache
JCache
LINQ
Proprietary native API

.Net

Supported programming languages

Java
Python

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

.Net

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

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

yes, but depending on the SQL-Server Edition

yes, with selectable consistency level

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)

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

optimistic locking and pessimistic 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 based on subaccounts and tokens

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

fine grained access rights according to SQL-standard

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Based on Windows Authentication

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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