DBMS > Altibase vs. Apache Cassandra vs. Google BigQuery vs. Google Cloud Bigtable

System Properties Comparison Altibase vs. Apache Cassandra vs. Google BigQuery vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Large scale data warehouse service with append-only tables

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

Primary database model

Relational DBMS

Wide column store

Relational DBMS

Key-value store
Wide column store

Secondary database models

Vector DBMS

starting with release V5

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

Score	0.87
Rank	#200	Overall
	#93	Relational DBMS

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	2.97
Rank	#92	Overall
	#15	Key-value stores
	#8	Wide column stores

Website

altibase.com

cassandra.apache.org

cloud.google.com/bigquery

cloud.google.com/bigtable

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

cassandra.apache.org/doc/latest

cloud.google.com/bigquery/docs

cloud.google.com/bigtable/docs

Developer

Altibase

Apache Software Foundation

Apache top level project, originally developped by Facebook

Google

Initial release

1999

2008

2010

2015

Current release

v7.3, 2023, August 2023

5.0-rc1, July 2024

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache version 2

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

C++

Java

Server operating systems

AIX
HP-UX
Linux

BSD
Linux
OS X
Windows

hosted

Data scheme

yes

schema-free

yes

schema-free

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

yes

restricted

only equality queries, not always the best performing solution

SQL

Support of SQL

ANSI SQL-92

SQL-like SELECT, DML and DDL statements (CQL)

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

RESTful HTTP/JSON API

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

Supported programming languages

C
C++
Java

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

stored procedures and stored functions

user defined functions

in JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Representation of geographical distribution of servers is possible

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

Since BigQuery is designed for querying data

Atomic single-row operations

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per object

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

Google Cloud Identity & Access Management (IAM)

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

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
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Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
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Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Apache Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
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