DBMS > Apache Impala vs. Kingbase vs. Memcached vs. MySQL vs. Warp 10

System Properties Comparison Apache Impala vs. Kingbase vs. Memcached vs. MySQL vs. Warp 10

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

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

In-memory key-value store, originally intended for caching

Widely used open source RDBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Key-value store

Relational DBMS

Key/Value like access via memcached API

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	0.50
Rank	#257	Overall
	#119	Relational DBMS

Score	18.08
Rank	#32	Overall
	#4	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

Technical documentation

impala.apache.org/impala-docs.html

github.com/memcached/memcached/wiki

dev.mysql.com/doc

www.warp10.io/content/02_Getting_started

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

BeiJing KINGBASE Information technologies inc.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Oracle

since 2010, originally MySQL AB, then Sun

SenX

Initial release

2013

1999

2003

1995

2015

Current release

4.1.0, June 2022

V8.0, August 2021

1.6.27, May 2024

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

BSD license

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

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Implementation language

C++

C and Java

C and C++

Java

Server operating systems

Linux

Linux
Windows

FreeBSD
Linux
OS X
Unix
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

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

Standard with numerous extensions

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

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

Proprietary protocol

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

yes

proprietary syntax

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

Repcached, a Memcached patch, provides this functionallity

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

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

based on HBase

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

using SASL (Simple Authentication and Security Layer) protocol

Users with fine-grained authorization concept

no user groups or roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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