Nothing is more important to businesses than data. But how can organizations make the most of it? By implementing proven technologies that power advanced analytics and Business Intelligence tools. Here’s a short overview of two such technologies – Apache Hadoop and Snowflake – to help business owners decide which one is the best match for their unique requirements.
Table of contents:
- What is Apache Hadoop?
- What is Snowflake?
- Hadoop vs. Snowflake – comparison
- Hadoop vs. Snowflake – which one is better for your company?
What is Apache Hadoop?
Hadoop is an open-source framework developed by Doug Cutting at Yahoo! and made open source in 2012. Hadoop allows companies to implement a distributed processing of large data sets across clusters of computers using some simple programming models.
The idea behind Hadoop was enabling companies to scale up from single servers to thousands of machines offering local computation and storage. That way, businesses could solve problems that involve massive amounts of data and computation. No wonder that since 2012, Hadoop gained considerable traction as a possible replacement for data warehouse applications running on costly MPP appliances.
What is Snowflake?
Snowflake is a cloud-based data warehouse available in a pay-as-you-go model. This cloud-based data-warehousing startup was founded in 2012 and since then raised over $1.4 billion in venture capital.
Snowflake works like an analytic data warehouse provided as Software-as-a-Service (SaaS). It offers companies data warehouse capabilities that are fast, easy to use, and more flexible than traditional data warehouse offerings. Note that Snowflake’s data warehouse uses a new SQL database engine that comes with a unique architecture designed for the cloud.
Read more: What is Snowflake Database? Architecture and Key Concepts
Hadoop vs. Snowflake – comparison
Apache Hadoop | Snowflake | |
| What is it? | Open-source framework | Data warehouse |
| Where is it located? | On-premise | Cloud-based |
| Features | Hadoop offers no ACID compliance — it writes immutable files without allowing any updates or changes. To change a file, users need to read it in and write it out with the applied changes. That’s why Hadoop isn’t a good tool for handling ad-hoc queries. | Snowflake supports multiple concurrent read-consistent reads. It also supports updates in compliance with ACID. |
| Data storage | Hadoop breaks data down into fixed-sized blocks replicated across three nodes. It’s not a good solution for small data files under 1GB where the entire data set is usually held on a single node. | Snowflake stores data on variable-length micro-partitions. It can process both small data sets and terabytes of data with ease. |
| Scalability | Hadoop isn’t easily scalable. Users can add additional nodes to a Hadoop cluster, but the cluster size can only be increased – not reduced. | Snowflake can scale up from a small to large data warehouse within seconds, and the other way round. |
| Costs | Hadoop is complex and comes with significant costs (deployment, configuration, and maintenance). | In Snowflake, there’s no need to deploy any hardware or install/configure any software. |
| Free trial | Yes, the tool is free. | Yes, the free trial lasts 30 days. |
| Price | Free (open-source). | The pricing depends on the usage, per-second billing (discounts possible with pre-purchasing). |
Hadoop vs. Snowflake – which one is better for your company?
Hadoop is costly to deploy and manage and offers poor support for low latency queries many Business Intelligence users may need. Hadoop is a good solution for a data lake, an immutable data store of raw business data.
However, Snowflake is an excellent data lake platform as well, thanks to its support for real-time data ingestion and JSON. Snowflake offers high performance, query optimization, and low latency to stand out as one of the best data warehousing platforms on the market today. Although using it comes at a price, the deployment and maintenance are easier than with Hadoop.
At Codete, we have experience in implementing both Hadoop and Snowflake. Right now, we’re on our way to becoming Snowflake’s official technology partner.
If you have any questions, feel free to get in touch with us.
