DBMS > Apache Impala vs. Derby vs. Kingbase vs. Newts

System Properties Comparison Apache Impala vs. Derby vs. Kingbase vs. Newts

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Time Series DBMS based on Cassandra

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	12.45
Rank	#40	Overall
	#24	Relational DBMS

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	0.07
Rank	#375	Overall
	#41	Time Series DBMS

Website

impala.apache.org

db.apache.org/derby

www.kingbase.com.cn

opennms.github.io/newts

Technical documentation

impala.apache.org/impala-docs.html

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

github.com/OpenNMS/newts/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Apache Software Foundation

BeiJing KINGBASE Information technologies inc.

OpenNMS Group

Initial release

2013

1997

1999

2014

Current release

4.1.0, June 2022

10.17.1.0, November 2023

V8.0, August 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache version 2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C and Java

Java

Server operating systems

Linux

All OS with a Java VM

Linux
Windows

Linux
OS X
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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

Standard with numerous extensions

APIs and other access methods

JDBC
ODBC

JDBC

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

HTTP REST
Java API

Supported programming languages

All languages supporting JDBC/ODBC

Java

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Java Stored Procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes

selectable replication factor

based on Cassandra

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

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

fine grained access rights according to SQL-standard

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More resources

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