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DBMS > Apache Impala vs. FatDB vs. OpenTSDB vs. SQL.JS

System Properties Comparison Apache Impala vs. FatDB vs. OpenTSDB vs. SQL.JS

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Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Analytic DBMS for Hadoop

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Scalable Time Series DBMS based on HBase

Port of SQLite to JavaScript

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

Relational DBMS

Secondary database models

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Website

impala.apache.org

Technical documentation

impala.apache.org/impala-docs.html

opentsdb.net/docs/build/html/index.html

sql.js.org/documentation/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

FatCloud

currently maintained by Yahoo and other contributors

Alon Zakai

enhancements implemented by others

Initial release

2013

2012

2011

2012

Current release

4.1.0, June 2022

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

LGPL

Open Source

Cloud-based only

Only available as a cloud service

no

no

no

no

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C#

Java

JavaScript

Server operating systems

Linux

Windows

Linux
Windows

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

Data scheme

yes

schema-free

schema-free

yes

Typing

predefined data types such as float or date

yes

yes

numeric data for metrics, strings for tags

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.

no

no

no

Secondary indexes

yes

yes

no

SQL

Support of SQL

SQL-like DML and DDL statements

no

Via inetgration in SQL Server

no

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

HTTP API
Telnet API

JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC

C#

Erlang
Go
Java
Python
R
Ruby

JavaScript

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

via applications

no

no

Triggers

no

yes

via applications

no

no

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

selectable replication factor

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

no

no

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

none

Foreign keys

Referential integrity

no

no

no

yes

Transaction concepts

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

no

no

no

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes

yes

Durability

Support for making data persistent

yes

yes

yes

no

except by serializing a db to a file

In-memory capabilities

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

no

no

yes

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

no

Can implement custom security layer via applications

no

no

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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

Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Comparing Different Time-Series Databases
10 February 2022, hackernoon.com

MapR to help admins peer into dense Hadoop clusters
28 June 2016, SiliconANGLE News

A real-time processing revival - O'Reilly Radar
2 April 2015, O'Reilly Radar

provided by Google News

9 Best JavaScript and TypeScript ORMs for 2024 — SitePoint
22 March 2023, SitePoint

Execute millions of SQL statements in milliseconds in the browser with WebAssembly and Web Workers.
14 January 2017, hackernoon.com

SQLite On The Web: Absurd-sql
24 August 2021, Hackaday

In Praise Of SQLite
28 July 2022, iProgrammer

10 Low-Code Rules for Serious Coders
21 November 2022, Embedded Computing Design

provided by Google News

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