DBMS > CrateDB vs. Snowflake vs. YDB

System Properties Comparison CrateDB vs. Snowflake vs. YDB

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Editorial information provided by DB-Engines

Name

Description

Distributed Database based on Lucene

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

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS

Relational DBMS

Document store
Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.71
Rank	#227	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#10	Vector DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.33
Rank	#287	Overall
	#43	Document stores
	#132	Relational DBMS

Website

cratedb.com

www.snowflake.com

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

cratedb.com/docs

docs.snowflake.net/manuals/index.html

ydb.tech/en/docs

Developer

Crate

Snowflake Computing Inc.

Yandex

Initial release

2013

2014

2019

License

Commercial or Open Source

Open Source

commercial

Open Source

Apache 2.0; commercial license available

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

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

hosted

Linux

Data scheme

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

yes

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

Flexible Schema (defined schema, partial schema, 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, but no triggers and constraints, and PostgreSQL compatibility

yes

SQL-like query language (YQL)

APIs and other access methods

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

CLI Client
JDBC
ODBC

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

.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

JavaScript (Node.js)
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

user defined functions (Javascript)

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

yes

Active-passive shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

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

rights management via user accounts

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

Access rights defined for Yandex Cloud users

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