DBMS > Apache Impala vs. GBase vs. Graphite vs. ReductStore

System Properties Comparison Apache Impala vs. GBase vs. Graphite vs. ReductStore

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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.

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	10.63
Rank	#40	Overall
	#24	Relational DBMS

Score	1.11
Rank	#173	Overall
	#78	Relational DBMS

Score	5.19
Rank	#62	Overall
	#4	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Website

impala.apache.org

www.gbase.cn

github.com/graphite-project/graphite-web

github.com/reductstore
www.reduct.store

Technical documentation

impala.apache.org/impala-docs.html

graphite.readthedocs.io

www.reduct.store/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

General Data Technology Co., Ltd.

Chris Davis

ReductStore LLC

Initial release

2013

2004

2006

2023

Current release

4.1.0, June 2022

GBase 8a, GBase 8s, GBase 8c

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Open Source

Business Source License 1.1

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

Python

C++, Rust

Server operating systems

Linux

Linux
Unix

Docker
Linux
macOS
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

HTTP API
Sockets

HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

JavaScript (Node.js)
Python

C++
JavaScript (Node.js)
Python
Rust

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

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

none

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

locking

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.

User concepts

Access control

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

yes

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

Time Series DBMS as a new trend?
1 June 2015, Paul Andlinger

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Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera brings Apache Iceberg data lake format to its Data Platform
30 June 2022, SiliconANGLE News

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Try out the Graphite monitoring tool for time-series data
29 October 2019, TechTarget

The Billion Data Point Challenge: Building a Query Engine for High Cardinality Time Series Data
10 December 2018, Uber

Getting Started with Monitoring using Graphite
23 January 2015, InfoQ.com

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

Collecting, storing, and analyzing your DevOps workloads with open-source Telegraf, Amazon Timestream, and Grafana
25 November 2020, AWS Blog

provided by Google News

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