DBMS > Apache Pinot vs. CouchDB vs. LevelDB vs. Snowflake

System Properties Comparison Apache Pinot vs. CouchDB vs. LevelDB vs. Snowflake

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Editorial information provided by DB-Engines

Name

Description

Realtime distributed OLAP datastore, designed to answer OLAP queries with low latency

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

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

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	0.38
Rank	#275	Overall
	#126	Relational DBMS

Score	8.30
Rank	#47	Overall
	#7	Document stores

Score	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

pinot.apache.org

couchdb.apache.org

github.com/google/leveldb

www.snowflake.com

Technical documentation

docs.pinot.apache.org

docs.couchdb.org/en/stable

github.com/google/leveldb/blob/main/doc/index.md

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation and contributors

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Google

Snowflake Computing Inc.

Initial release

2015

2005

2011

2014

Current release

1.0.0, September 2023

3.3.3, December 2023

1.23, February 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache version 2

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Java

Erlang

C++

Server operating systems

All OS with a Java JDK11 or higher

Android
BSD
Linux
OS X
Solaris
Windows

Illumos
Linux
OS X
Windows

hosted

Data scheme

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

via views

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
Python

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

View functions in JavaScript

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

improved architecture with release 2.0

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users can be defined per database

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

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