DBMS > Alibaba Cloud Table Store vs. Amazon SimpleDB vs. BigchainDB vs. Cassandra vs. Spark SQL

System Properties Comparison Alibaba Cloud Table Store vs. Amazon SimpleDB vs. BigchainDB vs. Cassandra vs. Spark SQL

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

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Secondary database models

Vector DBMS

starting with release V5

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

Score	0.24
Rank	#310	Overall
	#12	Wide column stores

Score	1.88
Rank	#139	Overall
	#24	Key-value stores

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	103.86
Rank	#12	Overall
	#1	Wide column stores

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/simpledb

www.bigchaindb.com

cassandra.apache.org

spark.apache.org/sql

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/simpledb

bigchaindb.readthedocs.io/en/latest

cassandra.apache.org/doc/latest

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Alibaba

Amazon

Apache Software Foundation

Apache top level project, originally developped by Facebook

Apache Software Foundation

Initial release

2016

2007

2016

2008

2014

Current release

4.1.3, July 2023

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

AGPL v3

Open Source

Apache version 2

Open Source

Apache 2.0

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

Python

Java

Scala

Server operating systems

hosted

Linux

BSD
Linux
OS X
Windows

Linux
OS X
Windows

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.

Secondary indexes

yes

All columns are indexed automatically

restricted

only equality queries, not always the best performing solution

SQL

Support of SQL

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

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

RESTful HTTP API

CLI Client
RESTful HTTP API

Proprietary protocol

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

JDBC
ODBC

Supported programming languages

Java
Python

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

Java
Python
R
Scala

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding must be implemented in the application

Sharding

no "single point of failure"

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

selectable replication factor

Representation of geographical distribution of servers is possible

none

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 specified for read operations

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

Concurrent data updates can be detected by the application

Atomicity and isolation are supported for single operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

yes

Access rights for users can be defined per object

More information provided by the system vendor

Specific characteristics

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