DBMS > Amazon CloudSearch vs. Apache Impala vs. Snowflake vs. TigerGraph

System Properties Comparison Amazon CloudSearch vs. Apache Impala vs. Snowflake vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for Hadoop

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

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

Primary database model

Search engine

Relational DBMS

Graph DBMS

Secondary database models

Document store

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

Score	1.81
Rank	#137	Overall
	#12	Search engines

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/cloudsearch

impala.apache.org

www.snowflake.com

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/cloudsearch

impala.apache.org/impala-docs.html

docs.snowflake.net/manuals/index.html

docs.tigergraph.com

Developer

Amazon

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Snowflake Computing Inc.

Initial release

2012

2013

2014

2017

Current release

4.1.0, June 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

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

C++

Server operating systems

hosted

Linux

hosted

Linux

Data scheme

yes

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

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.

yes

Secondary indexes

yes

all search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-like query language (GSQL)

APIs and other access methods

HTTP API

JDBC
ODBC

CLI Client
JDBC
ODBC

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

Supported programming languages

All languages supporting JDBC/ODBC

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

automatic partitioning across Amazon Search Instance as required

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

managed transparently by AWS

selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

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, groups and roles

based on Apache Sentry and Kerberos

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

Role-based access control

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