DBMS > Alibaba Cloud Table Store vs. Apache Cassandra vs. Apache Drill vs. Faircom EDGE

System Properties Comparison Alibaba Cloud Table Store vs. Apache Cassandra vs. Apache Drill vs. Faircom EDGE

Please select another system to include it in the comparison.

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

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

FairCom EDGE is an Industry 4.0 solution built to integrate, collect, aggregate and synchronize mission-critical data in edge computing environments

Primary database model

Wide column store

Document store
Relational DBMS

Key-value store
Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	0.25
Rank	#294	Overall
	#12	Wide column stores

Score	98.94
Rank	#11	Overall
	#1	Wide column stores

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.02
Rank	#370	Overall
	#55	Key-value stores
	#157	Relational DBMS

Website

www.alibabacloud.com/product/table-store

cassandra.apache.org

drill.apache.org

www.faircom.com/products/faircom-edge

Technical documentation

www.alibabacloud.com/help/en/tablestore

cassandra.apache.org/doc/latest

drill.apache.org/docs

docs.faircom.com/docs/en/UUID-23d4f1fd-d213-f6d5-b92e-9b7475baa14e.html

Developer

Alibaba

Apache Software Foundation

Apache top level project, originally developped by Facebook

Apache Software Foundation

FairCom Corporation

Initial release

2016

2008

2012

1979

Current release

5.0-rc1, July 2024

1.20.3, January 2023

V3, October 2020

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2

commercial

Restricted, free version available

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

ANSI C, C++

Server operating systems

hosted

BSD
Linux
OS X
Windows

Linux
OS X
Windows

Android
Linux

ARM, x86
Raspbian
Windows

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

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

restricted

only equality queries, not always the best performing solution

yes

SQL

Support of SQL

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

SQL SELECT statement is SQL:2003 compliant

yes

ANSI SQL queries

APIs and other access methods

HTTP API

Proprietary protocol

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

JDBC
ODBC
RESTful HTTP API

ADO.NET
Direct SQL
IoT Microservice layer
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Supported programming languages

Java
Python

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C++

C
C#
C++
Java
JavaScript
PHP
Python
VB.Net

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

no "single point of failure"

Sharding

File partitioning

Customizable business rules for partitioning

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

yes

Synchronous and asynchronous realtime replication based on transaction logs

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

Immediate Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

when using SQL

Transaction concepts

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

Atomic single-row operations

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

across SQL and NoSQL

Durability

Support for making data persistent

yes

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users can be defined per object

Depending on the underlying data source

Fine grained user, group and file access rights managed across SQL (per ANSI standard) and NoSQL.

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

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...
» more

News

DataStax Named a Leader in The Forrester Wave™: Vector Databases, Q3 2024
23 September 2024

How to Build a Notion Clone with Astra DB and Mongoose
20 September 2024

How to Monitor DataStax-Powered RAG Applications with Fiddler
19 September 2024

How Knowledge Graph RAG Boosts LLM Results
18 September 2024

How to Chunk Text in JavaScript for Your RAG Application
18 September 2024

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.