DBMS > AgensGraph vs. EXASOL vs. GridDB vs. OpenSearch vs. Snowflake

System Properties Comparison AgensGraph vs. EXASOL vs. GridDB vs. OpenSearch vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Scalable in-memory time series database optimized for IoT and Big Data

A distributed, RESTful search and analytics engine forked from Elasticsearch and based on Apache Lucene

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

Primary database model

Graph DBMS
Relational DBMS

Secondary database models

Key-value store
Relational DBMS

Vector DBMS

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	16.36
Rank	#37	Overall
	#4	Search engines

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

bitnine.net/agensgraph

www.exasol.com

griddb.net

github.com/opensearch-project
opensearch.org

www.snowflake.com

Technical documentation

bitnine.net/documentation

www.exasol.com/resources

docs.griddb.net

opensearch.org/docs/latest

docs.snowflake.net/manuals/index.html

Developer

Bitnine Global Inc.

Exasol

Toshiba Corporation

Amazon Web Services

Snowflake Computing Inc.

Initial release

2016

2000

2013

2021

2014

Current release

2.1, December 2018

5.1, August 2022

2.5.0, January 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

Apache Version 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.

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Implementation language

C++

Java

Server operating systems

Linux
OS X
Windows

Linux

All OS with a Java VM

hosted

Data scheme

depending on used data model

yes

schema-free

Flexible type definitions. Once a type is defined, it is persistent

yes

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

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL

Support of SQL

yes

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like query language

yes

APIs and other access methods

Cypher Query Language
JDBC

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

Java
Lua
Python
R

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Elasticsearch client

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

yes

user defined functions

Triggers

yes

by using the 'percolation' feature

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID at container level

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.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

Access rights for users can be defined per database

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

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

OpenSearch is a highly scalable and extensible open-source software suite for search,...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Distributed as fully open source under Apache License, Version 2.0 (ALv2), OpenSearch...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

The OpenSearch platform is used across a broad range of search , analytics, and observability...
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

The OpenSearch Project offers open source software licensed under Apache License...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.