DBMS > Apache Impala vs. GBase vs. Memcached vs. RocksDB

System Properties Comparison Apache Impala vs. GBase vs. Memcached vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS

Key-value store

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

Technical documentation

impala.apache.org/impala-docs.html

github.com/memcached/memcached/wiki

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

General Data Technology Co., Ltd.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Facebook, Inc.

Initial release

2013

2004

2003

2013

Current release

4.1.0, June 2022

GBase 8a, GBase 8s, GBase 8c

1.6.25, March 2024

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

BSD license

Open Source

BSD

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, Java, Python

C++

Server operating systems

Linux

FreeBSD
Linux
OS X
Unix
Windows

Linux

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

Standard with numerous extensions

APIs and other access methods

JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

Proprietary protocol

C++ API
Java API

Supported programming languages

All languages supporting JDBC/ODBC

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

user defined functions

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

none

Repcached, a Memcached patch, provides this functionallity

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

ACID

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

yes

using SASL (Simple Authentication and Security Layer) protocol

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