DBMS > AlaSQL vs. JaguarDB vs. Lovefield vs. NSDb vs. Oracle NoSQL

System Properties Comparison AlaSQL vs. JaguarDB vs. Lovefield vs. NSDb vs. Oracle NoSQL

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Performant, highly scalable DBMS for AI and IoT applications

Embeddable relational database for web apps written in pure JavaScript

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Document store
Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Time Series DBMS

Document store
Key-value store
Relational DBMS

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

Score	0.49
Rank	#259	Overall
	#40	Document stores
	#120	Relational DBMS

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Score	0.32
Rank	#290	Overall
	#132	Relational DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Website

alasql.org

www.jaguardb.com

google.github.io/lovefield

nsdb.io

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

github.com/AlaSQL/alasql

www.jaguardb.com/support.html

github.com/google/lovefield/blob/master/docs/spec_index.md

nsdb.io/Architecture

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

Andrey Gershun & Mathias R. Wulff

DataJaguar, Inc.

Google

Oracle

Initial release

2014

2015

2014

2017

2011

Current release

3.3 July 2023

2.1.12, February 2017

23.3, December 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

GPL V3.0

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

C++

the server part. Clients available in other languages

JavaScript

Java, Scala

Java

Server operating systems

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

Linux

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

tested with Chrome, Firefox, IE, Safari

Linux
macOS

Linux
Solaris SPARC/x86

Data scheme

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

optional

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.

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

via JavaScript builder pattern

SQL-like query language

SQL-like DML and DDL statements

APIs and other access methods

JavaScript API

JDBC
ODBC

gRPC
HTTP REST
WebSocket

RESTful HTTP API

Supported programming languages

JavaScript

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript

Java
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

Using Apache Lucene

yes

In-memory capabilities

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

yes

using MemoryDB

yes

off heap cache

User concepts

Access control

rights management via user accounts

Access rights for users and roles

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