DBMS > Alibaba Cloud Table Store vs. Google BigQuery vs. Infobright vs. RavenDB vs. Transbase

System Properties Comparison Alibaba Cloud Table Store vs. Google BigQuery vs. Infobright vs. RavenDB vs. Transbase

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Open Source Operational and Transactional Enterprise NoSQL Document Database

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Secondary database models

Graph 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	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.02
Rank	#192	Overall
	#90	Relational DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

www.alibabacloud.com/product/table-store

cloud.google.com/bigquery

ignitetech.com/softwarelibrary/infobrightdb

ravendb.net

www.transaction.de/en/products/transbase.html

Technical documentation

www.alibabacloud.com/help/en/tablestore

cloud.google.com/bigquery/docs

ravendb.net/docs

www.transaction.de/en/products/transbase/features.html

Developer

Alibaba

Google

Ignite Technologies Inc.; formerly InfoBright Inc.

Hibernating Rhinos

Transaction Software GmbH

Initial release

2016

2010

2005

2010

1987

Current release

5.4, July 2022

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

AGPL version 3, commercial license available

commercial

free development license

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

C and C++

Server operating systems

hosted

Linux
Windows

Linux
macOS
Raspberry Pi
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

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.

Secondary indexes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

SQL-like query language (RQL)

yes

APIs and other access methods

HTTP API

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java
Python

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

ACID, Cluster-wide transaction available

yes

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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