DBMS > Apache Impala vs. Dragonfly vs. Kingbase

System Properties Comparison Apache Impala vs. Dragonfly vs. Kingbase

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Secondary database models

Document store

Document store
Spatial DBMS

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	0.44
Rank	#255	Overall
	#38	Key-value stores

Score	0.44
Rank	#258	Overall
	#117	Relational DBMS

Website

impala.apache.org

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.kingbase.com.cn

Technical documentation

impala.apache.org/impala-docs.html

www.dragonflydb.io/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

DragonflyDB team and community contributors

BeiJing KINGBASE Information technologies inc.

Initial release

2013

2023

1999

Current release

4.1.0, June 2022

1.0, March 2023

V8.0, August 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

BSL 1.1

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

C and Java

Server operating systems

Linux

Linux
Windows

Data scheme

yes

scheme-free

yes

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

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

Standard with numerous extensions

APIs and other access methods

JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protocol

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

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

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

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Lua

user defined functions

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

yes

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

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

Password-based authentication

fine grained access rights according to SQL-standard

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More resources

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