Move Upload Data Data into a Data Warehouse in Minutes

Panoply provides out of the box integration with dozens of popular data sources, allowing you to query and analyze your data instantly without requiring thousands of lines of custom code. While Panoply works with many popular storage and database solutions, including Amazon S3, MySQL, and Postgres, Panoply is also programmed to allow uploads of your own data files.

Many different types of files and data technologies can be uploaded directly to Panoply, including:

  • .csv
  • JSON
  • .accda
  • SFTP
  • .mdb (for legacy data).

Panoply’s machine learning and NLP system models automate the data management process so that no ETL process is necessary. For custom data uploads, Panoply has several SDKs that reduce development time substantially.

Once the data is uploaded, it is instantly available for analyses and can be combined with all other data sources. Fast and simple, Panoply makes it easier to manage your data without a sizeable data warehousing infrastructure.

Panoply makes it easy to analyze any data you upload

Why Panoply?

Use-Case Optimization

Analyzes queries and data – identifying the best configuration for each use case, adjusting it over time, and building indexes, sortkeys, diskeys, data types, vacuuming, and partitioning.

Query Optimization

Identifies queries that do not follow best practices – such as those that include nested loops or implicit casting – and rewrites them to an equivalent query requiring a fraction of the runtime or resources.

Server Optimization

Optimizes server configurations over time based on query patterns and by learning which server setup works best. The platform switches server types seamlessly and measures the resulting performance.

Updates, Upserts, and Deletions

Supports standard SQL update and upset operations out of the box – without worrying about vacuuming or rebuilding- unlike many analytical databases.

Semi-Structured Data Parsing

Supports semi-structured text values like nested JSON, user-agent strings, some standard log formats, CSV, and serialized Ruby objects – parsing these objects and normalizing them into a relational database design.

Nested Structures

Handles nested structures automatically, flattening them into several tables with a one-to- many relationship. The result is a ready-to- use relational database design for all current and future datasets.

Columnar Storage

Provides seamless data storage and management in a multitiered, columnar storage based on Amazon Redshift, Elasticsearch, and Hadoop or SS3.

Data Tracking and Alerts

Simplifies how you keep track of vast amounts of data – by identifying patterns, providing notification of anomalies, and generating alerts when the results of arbitrary SQL queries exceed predefined thresholds.

Backup and Recovery

Automatically backs up changes to data to a redundant S3 storage, optionally saved in two different availability zones across continents – enabling full recovery to any point in time.

From raw data to analysis in under 10 minutes

Sign up now for a demo or a free trial of the Panoply platform

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