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Hadoop vs SQLite: What are the differences?

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; SQLite: A software library that implements a self-contained, serverless, zero-configuration, transactional SQL database engine. SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Hadoop and SQLite belong to "Databases" category of the tech stack.

"Great ecosystem" is the primary reason why developers consider Hadoop over the competitors, whereas "Lightweight" was stated as the key factor in picking SQLite.

Hadoop is an open source tool with 9.18K GitHub stars and 5.74K GitHub forks. Here's a link to Hadoop's open source repository on GitHub.

Intuit, Coderus, and Infoshare are some of the popular companies that use SQLite, whereas Hadoop is used by Airbnb, Uber Technologies, and Spotify. SQLite has a broader approval, being mentioned in 313 company stacks & 470 developers stacks; compared to Hadoop, which is listed in 237 company stacks and 116 developer stacks.

- No public GitHub repository available -

What is Hadoop?

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.

What is SQLite?

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.
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    What are some alternatives to Hadoop and SQLite?
    Cassandra
    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    Elasticsearch
    Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
    Splunk
    Splunk Inc. provides the leading platform for Operational Intelligence. Customers use Splunk to search, monitor, analyze and visualize machine data.
    HBase
    Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop.
    See all alternatives
    Decisions about Hadoop and SQLite
    StackShare Editors
    StackShare Editors
    Prometheus
    Prometheus
    Chef
    Chef
    Consul
    Consul
    Memcached
    Memcached
    Hack
    Hack
    Swift
    Swift
    Hadoop
    Hadoop
    Terraform
    Terraform
    Airflow
    Airflow
    Apache Spark
    Apache Spark
    Kubernetes
    Kubernetes
    gRPC
    gRPC
    HHVM (HipHop Virtual Machine)
    HHVM (HipHop Virtual Machine)
    Presto
    Presto
    Kotlin
    Kotlin
    Apache Thrift
    Apache Thrift

    Since the beginning, Cal Henderson has been the CTO of Slack. Earlier this year, he commented on a Quora question summarizing their current stack.

    Apps
    • Web: a mix of JavaScript/ES6 and React.
    • Desktop: And Electron to ship it as a desktop application.
    • Android: a mix of Java and Kotlin.
    • iOS: written in a mix of Objective C and Swift.
    Backend
    • The core application and the API written in PHP/Hack that runs on HHVM.
    • The data is stored in MySQL using Vitess.
    • Caching is done using Memcached and MCRouter.
    • The search service takes help from SolrCloud, with various Java services.
    • The messaging system uses WebSockets with many services in Java and Go.
    • Load balancing is done using HAproxy with Consul for configuration.
    • Most services talk to each other over gRPC,
    • Some Thrift and JSON-over-HTTP
    • Voice and video calling service was built in Elixir.
    Data warehouse
    • Built using open source tools including Presto, Spark, Airflow, Hadoop and Kafka.
    Etc
    See more
    Daniel Quinn
    Daniel Quinn
    Senior Developer at Workfinder · | 2 upvotes · 31.7K views
    atThe Paperless ProjectThe Paperless Project
    SQLite
    SQLite
    PostgreSQL
    PostgreSQL

    SQLite is a tricky beast. It's great if you're working single-threaded, but a Terrible Idea if you've got more than one concurrent connection. You use it because it's easy to setup, light, and portable (it's just a file).

    In Paperless, we've built a self-hosted web application, so it makes sense to standardise on something small & light, and as we don't have to worry about multiple connections (it's just you using the app), it's a perfect fit.

    For users wanting to scale Paperless up to a multi-user environment though, we do provide the hooks to switch to PostgreSQL .

    See more
    Interest over time
    Reviews of Hadoop and SQLite
    No reviews found
    How developers use Hadoop and SQLite
    Avatar of Pinterest
    Pinterest uses HadoopHadoop

    The MapReduce workflow starts to process experiment data nightly when data of the previous day is copied over from Kafka. At this time, all the raw log requests are transformed into meaningful experiment results and in-depth analysis. To populate experiment data for the dashboard, we have around 50 jobs running to do all the calculations and transforms of data.

    Avatar of Romans Malinovskis
    Romans Malinovskis uses SQLiteSQLite

    We build queries in PHP with DSQL that work with SQLite. We also have SQLite data controller, so that you can build SQLite-based models.

    Avatar of Coolfront Technologies
    Coolfront Technologies uses SQLiteSQLite

    Used during the "build process" of Coolfront Mobile's Flat rate search engine database. Flat rate data that resides in Salesforce is transformed using SQLite into a format that is usable for our mobile Flat rate search engine (AKA: Charlie).

    Avatar of Sripathi Krishnan
    Sripathi Krishnan uses SQLiteSQLite

    RDBTools is a self-hosted application, and it is important that the installation process is simple. With SQLite, we create a new database file for every analysis. Once the analysis is done, the SQLite file can be thrown away easily.

    Avatar of Yelp
    Yelp uses HadoopHadoop

    in 2009 we open sourced mrjob, which allows any engineer to write a MapReduce job without contending for resources. We’re only limited by the amount of machines in an Amazon data center (which is an issue we’ve rarely encountered).

    Avatar of Pinterest
    Pinterest uses HadoopHadoop

    The massive volume of discovery data that powers Pinterest and enables people to save Pins, create boards and follow other users, is generated through daily Hadoop jobs...

    Avatar of Perljobs.Ru
    Perljobs.Ru uses SQLiteSQLite

    All the dynamic data (i.e.: jobs) is stored in a simple SQLite database.

    Все динамические данные (вакансии) хранятся в простой SQLite БД.

    Avatar of A. M. Douglas
    A. M. Douglas uses SQLiteSQLite

    There's really no call for something heavier for this site. SQLite is simple, easy to use and quite reliable given its age.

    Avatar of Robert Brown
    Robert Brown uses HadoopHadoop

    Importing/Exporting data, interpreting results. Possible integration with SAS

    Avatar of Rohith Nandakumar
    Rohith Nandakumar uses HadoopHadoop

    TBD. Good to have I think. Analytics on loads of data, recommendations?

    How much does Hadoop cost?
    How much does SQLite cost?
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