DBMS > Apache Drill vs. PouchDB vs. RethinkDB vs. Rockset vs. Snowflake

System Properties Comparison Apache Drill vs. PouchDB vs. RethinkDB vs. Rockset vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

JavaScript DBMS with an API inspired by CouchDB

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

A scalable, reliable search and analytics service in the cloud, built on RocksDB

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

Primary database model

Document store
Relational DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

Relational DBMS
Search engine

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

Technical documentation

drill.apache.org/docs

pouchdb.com/guides

rethinkdb.com/docs

docs.rockset.com

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

The Linux Foundation

since July 2017

Rockset

Snowflake Computing Inc.

Initial release

2012

2009

2019

2014

Current release

1.20.3, January 2023

7.1.1, June 2019

2.4.1, August 2020

License

Commercial or Open Source

Open Source

Apache Version 2

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

JavaScript

C++

Server operating systems

Linux
OS X
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Windows

hosted

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

dynamic typing

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.

ingestion from XML files supported

yes

Secondary indexes

yes

via views

yes

all fields are automatically indexed

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

Read-only SQL queries, including JOINs

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP REST

only for PouchDB Server
JavaScript API

HTTP REST

CLI Client
JDBC
ODBC

Supported programming languages

C++

JavaScript

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

user defined functions

Triggers

yes

Client-side triggers through changefeeds

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

with a proxy-based framework, named couchdb-lounge

Sharding

range based

Automatic sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

by using IndexedDB, WebSQL or LevelDB as backend

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

yes

users and table-level permissions

Access rights for users and organizations can be defined via Rockset console

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

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