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Datomic vs Hadoop: What are the differences?
Datomic: The fully transactional, cloud-ready, distributed database. Build flexible, distributed systems that can leverage the entire history of your critical data, not just the most current state. Build them on your existing infrastructure or jump straight to the cloud; Hadoop: Open-source software for reliable, scalable, distributed computing. The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets 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.
Datomic and Hadoop belong to "Databases" category of the tech stack.
Hadoop is an open source tool with 9.26K GitHub stars and 5.78K GitHub forks. Here's a link to Hadoop's open source repository on GitHub.
Airbnb, Uber Technologies, and Spotify are some of the popular companies that use Hadoop, whereas Datomic is used by Rareburg, Exicon, and Yieldbot. Hadoop has a broader approval, being mentioned in 237 company stacks & 127 developers stacks; compared to Datomic, which is listed in 7 company stacks and 5 developer stacks.
I have a lot of data that's currently sitting in a MariaDB database, a lot of tables that weigh 200gb with indexes. Most of the large tables have a date column which is always filtered, but there are usually 4-6 additional columns that are filtered and used for statistics. I'm trying to figure out the best tool for storing and analyzing large amounts of data. Preferably self-hosted or a cheap solution. The current problem I'm running into is speed. Even with pretty good indexes, if I'm trying to load a large dataset, it's pretty slow.
Druid Could be an amazing solution for your use case, My understanding, and the assumption is you are looking to export your data from MariaDB for Analytical workload. It can be used for time series database as well as a data warehouse and can be scaled horizontally once your data increases. It's pretty easy to set up on any environment (Cloud, Kubernetes, or Self-hosted nix system). Some important features which make it a perfect solution for your use case. 1. It can do streaming ingestion (Kafka, Kinesis) as well as batch ingestion (Files from Local & Cloud Storage or Databases like MySQL, Postgres). In your case MariaDB (which has the same drivers to MySQL) 2. Columnar Database, So you can query just the fields which are required, and that runs your query faster automatically. 3. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. 4. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures 5. Gives ana amazing centralized UI to manage data sources, query, tasks.
Pros of Datomic
Pros of Hadoop
- Great ecosystem39
- One stack to rule them all11
- Great load balancer4
- Amazon aws1
- Java syntax1
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What is Datomic?
What is Hadoop?
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