HBase vs Microsoft SQL Server

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HBase
HBase

196
161
+ 1
12
Microsoft SQL Server
Microsoft SQL Server

3.9K
2.7K
+ 1
525
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HBase vs Microsoft SQL Server: What are the differences?

HBase: The Hadoop database, a distributed, scalable, big data store. 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; Microsoft SQL Server: A relational database management system developed by Microsoft. Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

HBase and Microsoft SQL Server can be primarily classified as "Databases" tools.

"Performance" is the primary reason why developers consider HBase over the competitors, whereas "Reliable and easy to use" was stated as the key factor in picking Microsoft SQL Server.

HBase is an open source tool with 2.91K GitHub stars and 2.01K GitHub forks. Here's a link to HBase's open source repository on GitHub.

According to the StackShare community, Microsoft SQL Server has a broader approval, being mentioned in 478 company stacks & 443 developers stacks; compared to HBase, which is listed in 54 company stacks and 18 developer stacks.

- No public GitHub repository available -

What is 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.

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.
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Why do developers choose HBase?
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    What are some alternatives to HBase and Microsoft SQL Server?
    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.
    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.
    Druid
    Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
    Apache Hive
    Hive facilitates reading, writing, and managing large datasets residing in distributed storage using SQL. Structure can be projected onto data already in storage.
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    Decisions about HBase and Microsoft SQL Server
    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
    Interest over time
    Reviews of HBase and Microsoft SQL Server
    No reviews found
    How developers use HBase and Microsoft SQL Server
    Avatar of Pinterest
    Pinterest uses HBaseHBase

    The final output is inserted into HBase to serve the experiment dashboard. We also load the output data to Redshift for ad-hoc analysis. For real-time experiment data processing, we use Storm to tail Kafka and process data in real-time and insert metrics into MySQL, so we could identify group allocation problems and send out real-time alerts and metrics.

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

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

    Avatar of Axibase
    Axibase uses HBaseHBase
    • Raw storage engine
    • Replication
    • Fault-tolerance
    Avatar of Mehdi TAZI
    Mehdi TAZI uses HBaseHBase

    Range scan and HDFS Buffering system

    Avatar of anerudhbalaji
    anerudhbalaji uses HBaseHBase

    Primary datastore

    How much does HBase cost?
    How much does Microsoft SQL Server cost?
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