DBMS > Alibaba Cloud Table Store vs. Google BigQuery vs. Teradata vs. TerminusDB vs. VelocityDB

System Properties Comparison Alibaba Cloud Table Store vs. Google BigQuery vs. Teradata vs. TerminusDB 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

Large scale data warehouse service with append-only tables

A hybrid cloud data analytics software platform (Teradata Vantage)

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

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

Primary database model

Wide column store

Relational DBMS

Graph DBMS

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
RDF store

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.05
Rank	#358	Overall
	#36	Graph DBMS
	#16	Object oriented DBMS

Website

www.alibabacloud.com/product/table-store

cloud.google.com/bigquery

www.teradata.com

terminusdb.com

velocitydb.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

cloud.google.com/bigquery/docs

docs.teradata.com

terminusdb.github.io/terminusdb/#

velocitydb.com/UserGuide

Developer

Alibaba

Google

Teradata

DataChemist Ltd.

VelocityDB Inc

Initial release

2016

2010

1984

2018

2011

Current release

Teradata Vantage 1.0 MU2, January 2019

11.0.0, January 2023

7.x

License

Commercial or Open Source

commercial

Open Source

GPL V3

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

Prolog, Rust

Server operating systems

hosted

hosted
Linux

Linux

Any that supports .NET

Data scheme

schema-free

yes

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

yes

SQL

Support of SQL

yes

SQL 2016 + extensions

SQL-like query language (WOQL)

APIs and other access methods

HTTP API

RESTful HTTP/JSON API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

.Net

Supported programming languages

Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

JavaScript
Python

.Net

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

UDFs, stored procedures, table functions in parallel

yes

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Hashing

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Role-based access control

Based on Windows Authentication

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