DBMS > Alibaba Cloud Table Store vs. Google Cloud Bigtable vs. H2 vs. Microsoft SQL Server vs. Vertica

System Properties Comparison Alibaba Cloud Table Store vs. Google Cloud Bigtable vs. H2 vs. Microsoft SQL Server vs. Vertica

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Microsofts flagship relational DBMS

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Wide column store

Key-value store
Wide column store

Relational DBMS

Column oriented

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS
Time Series DBMS

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	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	10.06
Rank	#42	Overall
	#26	Relational DBMS

Website

www.alibabacloud.com/product/table-store

cloud.google.com/bigtable

www.h2database.com

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

www.vertica.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

cloud.google.com/bigtable/docs

www.h2database.com/html/main.html

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

vertica.com/documentation

Developer

Alibaba

Google

Thomas Mueller

Microsoft

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2016

2015

2005

1989

2005

Current release

2.2.220, July 2023

SQL Server 2022, November 2022

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

restricted free version is available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

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Implementation language

Java

C++

Server operating systems

hosted

All OS with a Java VM

Linux
Windows

Linux

Data scheme

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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.

yes

Secondary indexes

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

HTTP API

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

JDBC
ODBC

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

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

Java
Python

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

Java

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

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

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

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

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

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

horizontal partitioning, hierarchical partitioning

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

With clustering: 2 database servers on different computers operate on identical copies of a database

yes, but depending on the SQL-Server Edition

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

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

Foreign keys

Referential integrity

yes

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

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
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Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
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