DBMS > Apache Impala vs. DolphinDB vs. mSQL vs. Yanza

System Properties Comparison Apache Impala vs. DolphinDB vs. mSQL vs. Yanza

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Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Analytic DBMS for Hadoop

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

mSQL (Mini SQL) is a simple and lightweight RDBMS

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Document store

Relational DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	1.27
Rank	#169	Overall
	#76	Relational DBMS

Website

impala.apache.org

www.dolphindb.com

hughestech.com.au/products/msql

yanza.com

Technical documentation

impala.apache.org/impala-docs.html

docs.dolphindb.cn/en/help200/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DolphinDB, Inc

Hughes Technologies

Yanza

Initial release

2013

2018

1994

2015

Current release

4.1.0, June 2022

v2.00.4, January 2022

4.4, October 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

free community version available

commercial

free licenses can be provided

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Windows

Data scheme

yes

schema-free

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

SQL-like query language

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

JDBC
ODBC

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

JDBC
ODBC

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C++
Delphi
Java
Perl
PHP
Tcl

any language that supports HTTP calls

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

Administrators, Users, Groups

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More resources

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

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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
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provided by Google News

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