DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Bangdb vs. Fauna vs. FeatureBase

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Bangdb vs. Fauna vs. FeatureBase

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, scalable database service by Amazon with the data stored in Amazons cloud

Converged and high performance database for device data, events, time series, document and graph

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

Primary database model

Wide column store

Document store
Key-value store

Document store
Graph DBMS
Time Series DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.22
Rank	#309	Overall
	#139	Relational DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

bangdb.com

fauna.com

www.featurebase.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

docs.bangdb.com

docs.fauna.com

docs.featurebase.com

Developer

Alibaba

Amazon

Sachin Sinha, BangDB

Fauna, Inc.

Molecula and Pilosa Open Source Contributors

Initial release

2016

2012

2014

2017

Current release

BangDB 2.0, October 2021

2022, May 2022

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD 3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Scala

Server operating systems

hosted

Linux

hosted

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL queries

APIs and other access methods

HTTP API

RESTful HTTP API

Proprietary protocol
RESTful HTTP API

RESTful HTTP API

gRPC
JDBC
Kafka Connector
ODBC

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Java
Python

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Java
Python

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

by integration with AWS Lambda

yes, Notifications (with Streaming only)

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

horizontal partitioning

consistent hashing

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

ACID across one or more tables within a single AWS account and region

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

yes, using Linux fsync

In-memory capabilities

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

yes, run db with in-memory only mode

yes

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 (enterprise version only)

Identity management, authentication, and access control

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