Software Alternatives & Reviews

OpenTSDB VS Hadoop

Compare OpenTSDB VS Hadoop and see what are their differences

OpenTSDB logo OpenTSDB

OpenTSDB is a distributed, scalable Time Series Database (TSDB) written on top of HBase.

Hadoop logo Hadoop

Open-source software for reliable, scalable, distributed computing
  • OpenTSDB Landing page
    Landing page //
    2021-09-26
  • Hadoop Landing page
    Landing page //
    2021-09-17

OpenTSDB videos

OpenTSDB - Time Series Schema on Schemaless NoSQL

More videos:

  • Review - OpenTSDB: A Scalable, Distributed Time Series Database

Hadoop videos

What is Big Data and Hadoop?

More videos:

  • Review - Product Ratings on Customer Reviews Using HADOOP.
  • Tutorial - Hadoop Tutorial For Beginners | Hadoop Ecosystem Explained in 20 min! - Frank Kane

Category Popularity

0-100% (relative to OpenTSDB and Hadoop)
Databases
36 36%
64% 64
Time Series Database
100 100%
0% 0
Big Data
0 0%
100% 100
Monitoring Tools
100 100%
0% 0

User comments

Share your experience with using OpenTSDB and Hadoop. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare OpenTSDB and Hadoop

OpenTSDB Reviews

4 Best Time Series Databases To Watch in 2019
OpenTSDB has been running for quite more time than its competitors and is one of the first technologies to address the need to store time series data at a very large scale. OpenTSDB promises to be able to store hundreds of billions of data rows over distributed instances of TSD servers.
Source: medium.com

Hadoop Reviews

A List of The 16 Best ETL Tools And Why To Choose Them
Companies considering Hadoop should be aware of its costs. A significant portion of the cost of implementing Hadoop comes from the computing power required for processing and the expertise needed to maintain Hadoop ETL, rather than the tools or storage themselves.
16 Top Big Data Analytics Tools You Should Know About
Hadoop is an Apache open-source framework. Written in Java, Hadoop is an ecosystem of components that are primarily used to store, process, and analyze big data. The USP of Hadoop is it enables multiple types of analytic workloads to run on the same data, at the same time, and on a massive scale on industry-standard hardware.
5 Best-Performing Tools that Build Real-Time Data Pipeline
Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than relying on hardware to deliver high-availability, the library itself is...

Social recommendations and mentions

Based on our record, Hadoop seems to be more popular. It has been mentiond 15 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

OpenTSDB mentions (0)

We have not tracked any mentions of OpenTSDB yet. Tracking of OpenTSDB recommendations started around Mar 2021.

Hadoop mentions (15)

View more

What are some alternatives?

When comparing OpenTSDB and Hadoop, you can also consider the following products

InfluxData - Scalable datastore for metrics, events, and real-time analytics.

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

TimescaleDB - TimescaleDB is a time-series SQL database providing fast analytics, scalability, with automated data management on a proven storage engine.

Apache Cassandra - The Apache Cassandra database is the right choice when you need scalability and high availability without compromising performance.

Prometheus - An open-source systems monitoring and alerting toolkit.

Apache Flink - Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.