DBMS > BigchainDB vs. Google BigQuery vs. PouchDB vs. Rockset vs. Warp 10

System Properties Comparison BigchainDB vs. Google BigQuery vs. PouchDB vs. Rockset vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Large scale data warehouse service with append-only tables

JavaScript DBMS with an API inspired by CouchDB

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Relational DBMS
Search engine

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	2.28
Rank	#115	Overall
	#21	Document stores

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

www.bigchaindb.com

cloud.google.com/bigquery

pouchdb.com

rockset.com

www.warp10.io

Technical documentation

bigchaindb.readthedocs.io/en/latest

cloud.google.com/bigquery/docs

pouchdb.com/guides

docs.rockset.com

www.warp10.io/content/02_Getting_started

Developer

Google

Apache Software Foundation

Rockset

SenX

Initial release

2016

2010

2012

2019

2015

Current release

7.1.1, June 2019

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

commercial

Open Source

Apache License 2.0

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

Python

JavaScript

C++

Java

Server operating systems

Linux

hosted

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

hosted

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

Secondary indexes

yes

via views

all fields are automatically indexed

SQL

Support of SQL

yes

Read-only SQL queries, including JOINs

APIs and other access methods

CLI Client
RESTful HTTP API

RESTful HTTP/JSON API

HTTP REST

only for PouchDB Server
JavaScript API

HTTP REST

HTTP API
Jupyter
WebSocket

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

View functions in JavaScript

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

with a proxy-based framework, named couchdb-lounge

Automatic sharding

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

yes

selectable replication factor

based on HBase

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

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes,with MongoDB ord RethinkDB

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.

yes

User concepts

Access control

yes

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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