Now, when we talk about big data tools, multiple aspects come into the picture concerning it. For example how large the data sets are, what type of analysis we are going to do on the data sets, what is the expected output etc. Hence, broadly speaking we can categorize big data open source tools list in following categories: based on data stores, as development platforms, as development tools, integration tools, for analytics and reporting tools.
If we closely look into big data open source tools list, it can be bewildering. As organizations are rapidly developing new solutions to achieve the competitive advantage in the big data market, it is useful to concentrate on open source big data tools which are driving the big data industry.
Why There are So Many Open Source Big Data Tools in the Market?
No doubt, Hadoop is the one reason and its domination in the big data world as an open source big data platform. Hence, most of the active groups or organizations develop tools which are open source to increase the adoption possibility in the industry. Moreover, an open source tool is easy to download and use, free of any licensing overhead.If we closely look into big data open source tools list, it can be bewildering. As organizations are rapidly developing new solutions to achieve the competitive advantage in the big data market, it is useful to concentrate on open source big data tools which are driving the big data industry.
Open Source Big Data Tools
Based on the popularity and usability we have listed the following ten open source tools as the best open source big data tools in 2020.1. Hadoop
Apache Hadoop is the most prominent and used tool in big data industry with its enormous capability of large-scale processing data. This is 100% open source framework and runs on commodity hardware in an existing data center. Furthermore, it can run on a cloud infrastructure.2. Apache Spark
Apache Spark is the next hype in the industry among the big data tools. The key point of this open source big data tool is it fills the gaps of Apache Hadoop concerning data processing. Interestingly, Spark can handle both batch data and real-time data. As Spark does in-memory data processing, it processes data much faster than traditional disk processing. This is indeed a plus point for data analysts handling certain types of data to achieve the faster outcome.3. Apache Storm
Apache Storm is a distributed real-time framework for reliably processing the unbounded data stream. The framework supports any programming language..4. Cassandra
Apache Cassandra is a distributed type database to manage a large set of data across the servers. This is one of the best big data tools that mainly processes structured data sets. It provides highly available service with no single point of failure. Additionally, it has certain capabilities which no other relational database and any NoSQL database can provide.5. RapidMiner
RapidMiner is a software platform for data science activities and provides an integrated environment for:- Preparing data
- Machine learning
- Text mining
- Predictive analytics
- Deep learning
- Application development
- Prototyping
- Data preparation
- Visualization
- Predictive analytics
- Model validation
- Optimization
- Statistical modeling
- Evaluation
- Deployment