DBMS > AgensGraph vs. CrateDB vs. Drizzle vs. RavenDB vs. Snowflake

System Properties Comparison AgensGraph vs. CrateDB vs. Drizzle vs. RavenDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

Distributed Database based on Lucene

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Primary database model

Graph DBMS
Relational DBMS

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Document store

Relational DBMS

Secondary database models

Relational DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.17
Rank	#320	Overall
	#29	Graph DBMS
	#143	Relational DBMS

Score	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	2.68
Rank	#102	Overall
	#19	Document stores

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

bitnine.net/agensgraph

cratedb.com

ravendb.net

www.snowflake.com

Technical documentation

bitnine.net/documentation

cratedb.com/docs

ravendb.net/docs

docs.snowflake.net/manuals/index.html

Developer

Bitnine Global Inc.

Crate

Drizzle project, originally started by Brian Aker

Hibernating Rhinos

Snowflake Computing Inc.

Initial release

2016

2013

2008

2010

2014

Current release

2.1, December 2018

5.8.1, August 2024

7.2.4, September 2012

5.4, July 2022

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

GNU GPL

Open Source

AGPL version 3, commercial license available

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

Linux
OS X
Windows

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

FreeBSD
Linux
OS X

Linux
macOS
Raspberry Pi
Windows

hosted

Data scheme

depending on used data model

Flexible Schema (defined schema, partial schema, schema free)

yes

schema-free

yes

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

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

yes, but no triggers and constraints, and PostgreSQL compatibility

yes

with proprietary extensions

SQL-like query language (RQL)

yes

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

JDBC

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

C
C++
Java
PHP

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions (Javascript)

yes

user defined functions

Triggers

hooks for callbacks inside the server can be used.

yes

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

Configurable replication on table/partition-level

Multi-source replication
Source-replica replication

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Read-after-write consistency on record level

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

unique row identifiers can be used for implementing an optimistic concurrency control strategy

ACID

ACID, Cluster-wide transaction available

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

fine grained access rights according to SQL-standard

rights management via user accounts

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Authorization levels configured per client per database

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

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