DBMS > Amazon CloudSearch vs. Amazon DynamoDB vs. JanusGraph vs. Microsoft Azure Table Storage vs. TigerGraph

System Properties Comparison Amazon CloudSearch vs. Amazon DynamoDB vs. JanusGraph vs. Microsoft Azure Table Storage vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

A hosted search engine service by Amazon with the data stored in Amazons cloud

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

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

A Wide Column Store for rapid development using massive semi-structured datasets

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Search engine

Document store
Key-value store

Graph DBMS

Wide column store

Graph DBMS

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/cloudsearch

aws.amazon.com/dynamodb

janusgraph.org

azure.microsoft.com/en-us/services/storage/tables

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/cloudsearch

docs.aws.amazon.com/dynamodb

docs.janusgraph.org

docs.tigergraph.com

Developer

Amazon

Linux Foundation; originally developed as Titan by Aurelius

Microsoft

Initial release

2012

2017

2012

2017

Current release

0.6.3, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache 2.0

commercial

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

C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

hosted

Linux

Data scheme

yes

schema-free

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.

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language (GSQL)

APIs and other access methods

HTTP API

RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Clojure
Java
Python

.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

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

ACID

optimistic locking

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

yes

In-memory capabilities

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

User concepts

Access control

authentication via encrypted signatures

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

User authentification and security via Rexster Graph Server

Access rights based on private key authentication or shared access signatures

Role-based access control

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