Apache ParquetThe Apache Software Foundation
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Azure Table StorageMicrosoft
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Related Products
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About
We created Parquet to make the advantages of compressed, efficient columnar data representation available to any project in the Hadoop ecosystem. Parquet is built from the ground up with complex nested data structures in mind, and uses the record shredding and assembly algorithm described in the Dremel paper. We believe this approach is superior to simple flattening of nested namespaces. Parquet is built to support very efficient compression and encoding schemes. Multiple projects have demonstrated the performance impact of applying the right compression and encoding scheme to the data. Parquet allows compression schemes to be specified on a per-column level, and is future-proofed to allow adding more encodings as they are invented and implemented. Parquet is built to be used by anyone. The Hadoop ecosystem is rich with data processing frameworks, and we are not interested in playing favorites.
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About
Use Azure Table storage to store petabytes of semi-structured data and keep costs down. Unlike many data stores—on-premises or cloud-based—Table storage lets you scale up without having to manually shard your dataset. Availability also isn’t a concern: using geo-redundant storage, stored data is replicated three times within a region—and an additional three times in another region, hundreds of miles away. Table storage is excellent for flexible datasets—web app user data, address books, device information, and other metadata—and lets you build cloud applications without locking down the data model to particular schemas. Because different rows in the same table can have a different structure—for example, order information in one row, and customer information in another—you can evolve your application and table schema without taking it offline. Table storage embraces a strong consistency model.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Individuals requiring a columnar storage solution available to any project in the Hadoop ecosystem
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Audience
IT teams seeking a NoSQL key-value store for rapid development using massive semi-structured datasets
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Pricing
No information available.
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationThe Apache Software Foundation
Founded: 1999
United States
parquet.apache.org
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Company InformationMicrosoft
Founded: 1975
United States
azure.microsoft.com/en-us/services/storage/tables/#features
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Categories |
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Integrations
Autymate
Data Sentinel
SSIS Integration Toolkit
StarfishETL
Amazon SageMaker Data Wrangler
Apache DataFusion
Arroyo
Auth.js
Blotout
CSViewer
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Integrations
Autymate
Data Sentinel
SSIS Integration Toolkit
StarfishETL
Amazon SageMaker Data Wrangler
Apache DataFusion
Arroyo
Auth.js
Blotout
CSViewer
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