DBMS > Apache Impala vs. SQL.JS vs. Transwarp StellarDB

System Properties Comparison Apache Impala vs. SQL.JS vs. Transwarp StellarDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Port of SQLite to JavaScript

A distributed graph DBMS built for enterprise-level graph applications

Primary database model

Relational DBMS

Graph DBMS

Secondary database models

Document store

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Score	0.07
Rank	#371	Overall
	#39	Graph DBMS

Website

impala.apache.org

sql.js.org

www.transwarp.cn/en/product/stellardb

Technical documentation

impala.apache.org/impala-docs.html

sql.js.org/documentation/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Alon Zakai

enhancements implemented by others

Transwarp

Initial release

2013

2012

Current release

4.1.0, June 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

commercial

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

C++

JavaScript

Server operating systems

Linux

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

Data scheme

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

SQL-like query language

APIs and other access methods

JDBC
ODBC

JavaScript API

OpenCypher

Supported programming languages

All languages supporting JDBC/ODBC

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

except by serializing a db to a file

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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