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FoundationDB
FoundationDB

15
27
+ 1
12
Hadoop
Hadoop

1.5K
1.4K
+ 1
53
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FoundationDB vs Hadoop: What are the differences?

FoundationDB: Multi-model database with particularly strong fault tolerance, performance, and operational ease. FoundationDB is a NoSQL database with a shared nothing architecture. Designed around a "core" ordered key-value database, additional features and data models are supplied in layers. The key-value database, as well as all layers, supports full, cross-key and cross-server ACID transactions; 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.

FoundationDB and Hadoop can be categorized as "Databases" tools.

"ACID transactions" is the top reason why over 2 developers like FoundationDB, while over 34 developers mention "Great ecosystem" as the leading cause for choosing Hadoop.

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.

- No public GitHub repository available -

What is FoundationDB?

FoundationDB is a NoSQL database with a shared nothing architecture. Designed around a "core" ordered key-value database, additional features and data models are supplied in layers. The key-value database, as well as all layers, supports full, cross-key and cross-server ACID transactions.

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.
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Why do developers choose FoundationDB?
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      What tools integrate with FoundationDB?
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        What are some alternatives to FoundationDB and Hadoop?
        CockroachDB
        It allows you to deploy a database on-prem, in the cloud or even across clouds, all as a single store. It is a simple and straightforward bridge to your future, cloud-based data architecture.
        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.
        Redis
        Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
        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.
        Couchbase
        Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
        See all alternatives
        Decisions about FoundationDB and Hadoop
        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
        Interest over time
        Reviews of FoundationDB and Hadoop
        No reviews found
        How developers use FoundationDB and Hadoop
        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 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 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 FoundationDB cost?
        How much does Hadoop cost?
        Pricing unavailable
        News about FoundationDB
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