Hadoop vs Microsoft SQL Server vs Oracle

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Hadoop
Hadoop

1.5K
1.4K
+ 1
53
Microsoft SQL Server
Microsoft SQL Server

5.2K
4K
+ 1
531
Oracle
Oracle

985
754
+ 1
82
- No public GitHub repository available -
- 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 Microsoft SQL Server?

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

What is Oracle?

Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.
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Why do developers choose Hadoop?
Why do developers choose Microsoft SQL Server?
Why do developers choose Oracle?

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    What companies use Hadoop?
    What companies use Microsoft SQL Server?
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    What tools integrate with Hadoop?
    What tools integrate with Microsoft SQL Server?
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    What are some alternatives to Hadoop, Microsoft SQL Server, and Oracle?
    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.
    Snowflake
    Snowflake eliminates the administration and management demands of traditional data warehouses and big data platforms. Snowflake is a true data warehouse as a service running on Amazon Web Services (AWS)—no infrastructure to manage and no knobs to turn.
    See all alternatives
    Decisions about Hadoop, Microsoft SQL Server, and Oracle
    AWS Elastic Beanstalk
    AWS Elastic Beanstalk
    Heroku
    Heroku
    Ruby
    Ruby
    Rails
    Rails
    Amazon RDS for PostgreSQL
    Amazon RDS for PostgreSQL
    MariaDB
    MariaDB
    Microsoft SQL Server
    Microsoft SQL Server
    Amazon RDS
    Amazon RDS
    AWS Lambda
    AWS Lambda
    Python
    Python
    Redis
    Redis
    Memcached
    Memcached
    AWS Elastic Load Balancing (ELB)
    AWS Elastic Load Balancing (ELB)
    Amazon Elasticsearch Service
    Amazon Elasticsearch Service
    Amazon ElastiCache
    Amazon ElastiCache

    We initially started out with Heroku as our PaaS provider due to a desire to use it by our original developer for our Ruby on Rails application/website at the time. We were finding response times slow, it was painfully slow, sometimes taking 10 seconds to start loading the main page. Moving up to the next "compute" level was going to be very expensive.

    We moved our site over to AWS Elastic Beanstalk , not only did response times on the site practically become instant, our cloud bill for the application was cut in half.

    In database world we are currently using Amazon RDS for PostgreSQL also, we have both MariaDB and Microsoft SQL Server both hosted on Amazon RDS. The plan is to migrate to AWS Aurora Serverless for all 3 of those database systems.

    Additional services we use for our public applications: AWS Lambda, Python, Redis, Memcached, AWS Elastic Load Balancing (ELB), Amazon Elasticsearch Service, Amazon ElastiCache

    See more
    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
    Erin G
    Erin G
    Linux
    Linux
    PostgreSQL
    PostgreSQL
    MySQL
    MySQL
    Microsoft SQL Server
    Microsoft SQL Server

    I am a Microsoft SQL Server programmer who is a bit out of practice. I have been asked to assist on a new project. The overall purpose is to organize a large number of recordings so that they can be searched. I have an enormous music library but my songs are several hours long. I need to include things like time, date and location of the recording. I don't have a problem with the general database design. I have two primary questions:

    1. I need to use either MySQL or PostgreSQL on a Linux based OS. Which would be better for this application?
    2. I have not dealt with a sound based data type before. How do I store that and put it in a table? Thank you.
    See more
    Interest over time
    Reviews of Hadoop, Microsoft SQL Server, and Oracle
    No reviews found
    How developers use Hadoop, Microsoft SQL Server, and Oracle
    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 Brillium, Inc.
    Brillium, Inc. uses Microsoft SQL ServerMicrosoft SQL Server

    We've always counted on SQL Server as our database backend. It has served us well over the years. It isn't the cheapest part of our stack, but with the plethora of tools provided by 3rd parties, we have found an incredible and scalable method of keeping our data available and easy to maintain.

    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 Andrew Miller
    Andrew Miller uses Microsoft SQL ServerMicrosoft SQL Server

    Defacto, industry standard for backend relational databases. Entity Framework makes designing, migrating & maintaining SQL Server databases a breeze. LocalDB is especially helpful during development.

    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 David Flynn
    David Flynn uses Microsoft SQL ServerMicrosoft SQL Server

    Our core systems that we integrate with are using SQL Server 2012 / 2016 database servers. We use database views on core system databases to help build our domain model.

    Avatar of Olo
    Olo uses Microsoft SQL ServerMicrosoft SQL Server

    Main transactional database. SQL Server 2012 Enterprise with AlwaysOn Availability Groups for high availability and disaster recovery.

    Avatar of Onezino Gabriel
    Onezino Gabriel uses OracleOracle

    Gerenciamento de banco de dados utilizados por odos os serviços/aplicações criados

    Avatar of Robert Brown
    Robert Brown uses HadoopHadoop

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

    Avatar of Adrian Harabulă
    Adrian Harabulă uses OracleOracle

    recommended solution at school, also used to try out alternatives to MySQL

    Avatar of Rohith Nandakumar
    Rohith Nandakumar uses HadoopHadoop

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

    Avatar of Arbor Health, LLC
    Arbor Health, LLC uses Microsoft SQL ServerMicrosoft SQL Server

    Managing script output and input, as well as data cleansing.

    Avatar of Satoru Ishikawa
    Satoru Ishikawa uses OracleOracle

    データベース構成設計や実際のデータ操作など。実作業では9i, 10g, 11gを触った。

    Avatar of Hyunwoo Shim
    Hyunwoo Shim uses OracleOracle

    Oracle을 통해 RDB를 학습하였습니다.

    Avatar of douglasresende
    douglasresende uses OracleOracle

    I'm expert database.

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