DBMS > AgensGraph vs. Amazon CloudSearch vs. Apache IoTDB vs. OrigoDB vs. Snowflake

System Properties Comparison AgensGraph vs. Amazon CloudSearch vs. Apache IoTDB vs. OrigoDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

A fully ACID in-memory object graph database

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Graph DBMS
Relational DBMS

Search engine

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/cloudsearch

iotdb.apache.org

origodb.com

www.snowflake.com

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/cloudsearch

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

origodb.com/docs

docs.snowflake.net/manuals/index.html

Developer

Bitnine Global Inc.

Amazon

Apache Software Foundation

Robert Friberg et al

Snowflake Computing Inc.

Initial release

2016

2012

2018

2009

under the name LiveDB

2014

Current release

2.1, December 2018

1.1.0, April 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Apache Version 2.0

Open Source

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

Java

Server operating systems

Linux
OS X
Windows

hosted

All OS with a Java VM (>= 1.8)

Linux
Windows

hosted

Data scheme

depending on used data model

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

Cypher Query Language
JDBC

HTTP API

JDBC
Native API

.NET Client API
HTTP API
LINQ

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

C
C#
C++
Go
Java
Python
Scala

.Net

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Domain Events

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

yes

automatic partitioning across Amazon Search Instance as required

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

horizontal partitioning

client side managed; servers are not synchronized

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

managed transparently by AWS

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

authentication via encrypted signatures

yes

Role based authorization

Users with fine-grained authorization concept, user roles and pluggable authentication

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