DBMS > AgensGraph vs. ClickHouse vs. Snowflake vs. SurrealDB

System Properties Comparison AgensGraph vs. ClickHouse vs. Snowflake vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Description

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

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Document store
Graph DBMS

Secondary database models

Time Series 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	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

bitnine.net/agensgraph

clickhouse.com

www.snowflake.com

surrealdb.com

Technical documentation

bitnine.net/documentation

clickhouse.com/docs

docs.snowflake.net/manuals/index.html

surrealdb.com/docs

Developer

Bitnine Global Inc.

Clickhouse Inc.

Snowflake Computing Inc.

SurrealDB Ltd

Initial release

2016

2014

2022

Current release

2.1, December 2018

v24.4.2.141-stable, June 2024

v1.5.0, May 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

Apache 2.0

commercial

Open Source

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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ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

C++

Rust

Server operating systems

Linux
OS X
Windows

FreeBSD
Linux
macOS

hosted

Linux
macOS
Windows

Data scheme

depending on used data model

yes

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

schema-free

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

SQL

Support of SQL

yes

Close to ANSI SQL (SQL/JSON + extensions)

yes

SQL-like query language

APIs and other access methods

Cypher Query Language
JDBC

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

CLI Client
JDBC
ODBC

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

C
Java
JavaScript
Python

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

JavaScript (Node.js)
Python

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

key based and custom

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

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

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 and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

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

yes, based on authentication and database rules

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