DBMS > Apache Impala vs. Blueflood vs. ReductStore vs. Tibero

System Properties Comparison Apache Impala vs. Blueflood vs. ReductStore vs. Tibero

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Scalable TimeSeries DBMS based on Cassandra

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.

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

Time Series DBMS

Relational 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	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	1.46
Rank	#151	Overall
	#70	Relational DBMS

Website

impala.apache.org

blueflood.io

github.com/reductstore
www.reduct.store

us.tmaxsoft.com/products/tibero

Technical documentation

impala.apache.org/impala-docs.html

github.com/rax-maas/blueflood/wiki

www.reduct.store/docs

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Rackspace

ReductStore LLC

TmaxSoft

Initial release

2013

2023

2003

Current release

4.1.0, June 2022

1.9, March 2024

7, September 2022

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Business Source License 1.1

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C++, Rust

C and Assembler

Server operating systems

Linux

Linux
OS X

Docker
Linux
macOS
Windows

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

predefined scheme

yes

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

APIs and other access methods

JDBC
ODBC

HTTP REST

HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

All languages supporting JDBC/ODBC

C++
JavaScript (Node.js)
Python
Rust

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

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.

planned for next version

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 (SQL 92, SQL 99)

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

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 Bringing Impala to AWS Cloud
28 November 2017, Datanami

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

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

provided by Google News

[Herald Interview] TmaxTibero eyes global expansion with certified DBMS tech
11 August 2024, The Korea Herald

TmaxData to supply database management software to Hyundai, Kia
12 June 2019, 코리아타임스

How to Succeed at Large-Scale Mainframe Replatforming with TmaxSoft OpenFrame on AWS
2 August 2022, AWS Blog

Hyundai and Kia Say Good-bye to Oracle and Choose Tmax as DBMS Vendor
13 June 2019, BusinessKorea

AIS Partners TmaxSoft to Offer Database-as-a-Service on PaaS Cloud for Enterprise Customers
7 December 2017, The Fast Mode

provided by Google News

Share this page