DBMS > Derby vs. Google BigQuery vs. LokiJS vs. PouchDB vs. RisingWave

System Properties Comparison Derby vs. Google BigQuery vs. LokiJS vs. PouchDB vs. RisingWave

Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Large scale data warehouse service with append-only tables

In-memory JavaScript DBMS

JavaScript DBMS with an API inspired by CouchDB

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Relational DBMS

Document store

Relational DBMS

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	2.34
Rank	#112	Overall
	#21	Document stores

Score	0.64
Rank	#238	Overall
	#110	Relational DBMS

Website

db.apache.org/derby

cloud.google.com/bigquery

github.com/techfort/LokiJS

pouchdb.com

www.risingwave.com/database

Technical documentation

db.apache.org/derby/manuals/index.html

cloud.google.com/bigquery/docs

techfort.github.io/LokiJS

pouchdb.com/guides

docs.risingwave.com/docs/current/intro

Developer

Apache Software Foundation

Google

Apache Software Foundation

RisingWave Labs

Initial release

1997

2010

2014

2012

2022

Current release

10.17.1.0, November 2023

7.1.1, June 2019

1.2, September 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Open Source

Apache Version 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

Java

JavaScript

Rust

Server operating systems

All OS with a Java VM

hosted

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

Docker
Linux
macOS

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Standard SQL-types and JSON

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

yes

via views

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC

RESTful HTTP/JSON API

JavaScript API

HTTP REST

only for PouchDB Server
JavaScript API

JDBC
PostgreSQL wire protocol

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

View functions in JavaScript

UDFs in Python or Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

with a proxy-based framework, named couchdb-lounge

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication

also with CouchDB databases
Source-replica replication

also with CouchDB databases

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

atomic operations within a single collection possible

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

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

fine grained access rights according to SQL-standard

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

Google Cloud Identity & Access Management (IAM)

Users and Roles

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