Amazon DynamoDBย vsย HBase

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Amazon DynamoDB
Amazon DynamoDB

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HBase

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Amazon DynamoDB vs HBase: What are the differences?

Developers describe Amazon DynamoDB as "Fully managed NoSQL database service". All data items are stored on Solid State Drives (SSDs), and are replicated across 3 Availability Zones for high availability and durability. With DynamoDB, you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use. On the other hand, HBase is detailed as "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.

Amazon DynamoDB can be classified as a tool in the "NoSQL Database as a Service" category, while HBase is grouped under "Databases".

"Predictable performance and cost" is the primary reason why developers consider Amazon DynamoDB over the competitors, whereas "Performance" was stated as the key factor in picking HBase.

HBase is an open source tool with 2.87K GitHub stars and 1.98K GitHub forks. Here's a link to HBase's open source repository on GitHub.

Lyft, New Relic, and Sellsuki are some of the popular companies that use Amazon DynamoDB, whereas HBase is used by SendGrid, HubSpot, and hike. Amazon DynamoDB has a broader approval, being mentioned in 430 company stacks & 173 developers stacks; compared to HBase, which is listed in 54 company stacks and 18 developer stacks.

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What is Amazon DynamoDB?

With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

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.
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Why do developers choose Amazon DynamoDB?
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    What are some alternatives to Amazon DynamoDB and HBase?
    Google Cloud Datastore
    Use a managed, NoSQL, schemaless database for storing non-relational data. Cloud Datastore automatically scales as you need it and supports transactions as well as robust, SQL-like queries.
    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.
    Amazon SimpleDB
    Developers simply store and query data items via web services requests and Amazon SimpleDB does the rest. Behind the scenes, Amazon SimpleDB creates and manages multiple geographically distributed replicas of your data automatically to enable high availability and data durability. Amazon SimpleDB provides a simple web services interface to create and store multiple data sets, query your data easily, and return the results. Your data is automatically indexed, making it easy to quickly find the information that you need. There is no need to pre-define a schema or change a schema if new data is added later. And scale-out is as simple as creating new domains, rather than building out new servers.
    MySQL
    The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.
    Amazon S3
    Amazon Simple Storage Service provides a fully redundant data storage infrastructure for storing and retrieving any amount of data, at any time, from anywhere on the web
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    Decisions about Amazon DynamoDB and HBase
    Doru Mihai
    Doru Mihai
    Solution Architect ยท | 4 upvotes ยท 454 views
    Amazon DynamoDB
    Amazon DynamoDB

    I use Amazon DynamoDB because it integrates seamlessly with other AWS SaaS solutions and if cost is the primary concern early on, then this will be a better choice when compared to AWS RDS or any other solution that requires the creation of a HA cluster of IaaS components that will cost money just for being there, the costs not being influenced primarily by usage.

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    Reviews of Amazon DynamoDB and HBase
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    How developers use Amazon DynamoDB and HBase
    Avatar of Karma
    Karma uses Amazon DynamoDBAmazon DynamoDB

    For most of the stuff we use MySQL. We just use Amazon RDS. But for some stuff we use Amazon DynamoDB. We love DynamoDB. It's amazing. We store usage data in there, for example. I think we have close to seven or eight hundred million records in there and it's scaled like you don't even notice it. You never notice any performance degradation whatsoever. It's insane, and the last time I checked we were paying $150 bucks for that.

    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 Volkan ร–zรงelik
    Volkan ร–zรงelik uses Amazon DynamoDBAmazon DynamoDB

    zerotoherojs.com โ€™s userbase, and course details are stored in DynamoDB tables.

    The good thing about AWS DynamoDB is: For the amount of traffic that I have, it is free. It is highly-scalable, it is managed by Amazon, and it is pretty fast.

    It is, again, one less thing to worry about (when compared to managing your own MongoDB elsewhere).

    Avatar of CloudRepo
    CloudRepo uses Amazon DynamoDBAmazon DynamoDB

    We store customer metadata in DynamoDB. We decided to use Amazon DynamoDB because it was a fully managed, highly available solution. We didn't want to operate our own SQL server and we wanted to ensure that we built CloudRepo on high availability components so that we could pass that benefit back to our customers.

    Avatar of nrise
    nrise uses Amazon DynamoDBAmazon DynamoDB

    ๋ช‡๋ช‡ ๋กœ๊ทธ๋Š” ํ˜„์žฌ AWS DynamoDB ์— ๊ธฐ๋ก๋˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ๊ฐœ์„ ์„ ํ†ตํ•ด mongodb ๋กœ ์˜ฎ๊ธธ ๊ณ„ํš์„ ํ•˜๊ณ  ์žˆ์Šต๋‹ˆ๋‹ค. ์•„์ฃผ ๊ฐ„๋‹จํ•œ ๋ฐ์ดํ„ฐ๋ฅผ ์Œ“๋Š” ์šฉ๋„๋กœ๋Š” ๋‚˜์˜์ง€ ์•Š์Šต๋‹ˆ๋‹ค. ๋‹ค๋งŒ, ์ฟผ๋ฆฌ๊ฐ€ ์•„์ฃผ ์ œํ•œ์ ์ž…๋‹ˆ๋‹ค. ์‚ฌ์šฉํ•˜๊ธฐ ์ „์— ๋ฐ˜๋“œ์‹œ DynamoDB ์˜ ์ŠคํŽ™์„ ํ™•์ธํ•  ํ•„์š”๊ฐ€ ์žˆ์Šต๋‹ˆ๋‹ค.

    Avatar of HyperTrack
    HyperTrack uses Amazon DynamoDBAmazon DynamoDB

    To store device health records as it allows super fast writes and range queries.

    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

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