DBMS > Alibaba Cloud Table Store vs. Amazon DocumentDB vs. Amazon DynamoDB vs. Coveo vs. Titan

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DocumentDB vs. Amazon DynamoDB vs. Coveo vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Wide column store

Document store

Document store
Key-value store

Search engine

Graph DBMS

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

Score	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	1.91
Rank	#132	Overall
	#24	Document stores

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

Score	2.28
Rank	#114	Overall
	#11	Search engines

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/documentdb

aws.amazon.com/dynamodb

www.coveo.com

github.com/thinkaurelius/titan

Technical documentation

www.alibabacloud.com/help/en/tablestore

aws.amazon.com/documentdb/resources

docs.aws.amazon.com/dynamodb

docs.coveo.com

github.com/thinkaurelius/titan/wiki

Developer

Alibaba

Amazon

Coveo

Aurelius, owned by DataStax

Initial release

2016

2019

2012

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache license, version 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.

Implementation language

Java

Server operating systems

hosted

Linux
OS X
Unix
Windows

Data scheme

schema-free

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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

SQL

Support of SQL

APIs and other access methods

HTTP API

proprietary protocol using JSON (MongoDB compatible)

RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Java
Python

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
Java
JavaScript
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

Relationships in graph

Transaction concepts

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

Atomic single-row operations

Atomic single-document operations

ACID

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

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

granular access controls, API key management, content filters

User authentification and security via Rexster Graph Server

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