DBMS > Alibaba Cloud PolarDB vs. Apache Cassandra vs. BigObject vs. Drizzle

System Properties Comparison Alibaba Cloud PolarDB vs. Apache Cassandra vs. BigObject vs. Drizzle

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

A cloud-native relational database compatible with MySQL, PostgreSQL, and Oracle. Designed for business critical applications.

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Analytic DBMS for real-time computations and queries

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Primary database model

Relational DBMS

Wide column store

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	0.90
Rank	#197	Overall
	#92	Relational DBMS

Score	97.71
Rank	#11	Overall
	#1	Wide column stores

Score	0.13
Rank	#332	Overall
	#148	Relational DBMS

Website

www.alibabacloud.com/product/polardb

cassandra.apache.org

bigobject.io

Technical documentation

www.alibabacloud.com/help/en/polardb/product-overview

cassandra.apache.org/doc/latest

docs.bigobject.io

Developer

Alibaba

Apache Software Foundation

Apache top level project, originally developped by Facebook

BigObject, Inc.

Drizzle project, originally started by Brian Aker

Initial release

2008

2015

2008

Current release

5.0-rc1, July 2024

7.2.4, September 2012

License

Commercial or Open Source

commercial

Open Source

Apache version 2

commercial

free community edition available

Open Source

GNU GPL

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

Java

C++

Server operating systems

hosted

BSD
Linux
OS X
Windows

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
OS X

Data scheme

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.

yes

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

yes

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

SQL-like DML and DDL statements

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

Proprietary protocol

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

fluentd
ODBC
RESTful HTTP API

JDBC

Supported programming languages

Java
Python

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C
C++
Java
PHP

Server-side scripts

Stored procedures

yes

Lua

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

selectable replication factor

Representation of geographical distribution of servers is possible

none

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

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

none

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

More information provided by the system vendor

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Key customers

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Market metrics

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Licensing and pricing models

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