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  1. Stackups
  2. Application & Data
  3. Databases
  4. Big Data As A Service
  5. Panoply vs Stitch

Panoply vs Stitch

OverviewComparisonAlternatives

Overview

Stitch
Stitch
Stacks150
Followers150
Votes12
Panoply
Panoply
Stacks9
Followers17
Votes0

Panoply vs Stitch: What are the differences?

<Write Introduction here>
  1. Data Sources: Panoply supports a wide range of data sources including MySQL, PostgreSQL, Amazon Redshift, and more, while Stitch primarily focuses on extracting data from popular cloud services such as Google Analytics, Salesforce, and Zendesk.
  2. Data Transformation: Panoply offers more advanced data transformation capabilities like SQL-based transformations, data enrichment, and custom scripting, whereas Stitch provides basic transformation features like filtering and joining data.
  3. Real-time Data Pipelines: Stitch specializes in real-time data pipelines and streaming data integration, enabling users to sync and analyze data as it's generated, while Panoply focuses more on batch data processing and data warehousing.
  4. Scalability: Panoply is designed to handle large volumes of data effectively, making it more suitable for enterprises with complex data needs, whereas Stitch may be more suitable for small to medium-sized businesses with simpler data integration requirements.
  5. Cost Structure: Panoply offers a pricing model based on the amount of data processed, making it a more cost-effective option for organizations with unpredictable data volumes, whereas Stitch charges based on the number of connectors used, which may be more suitable for users with a fixed set of data sources.
  6. Data Storage: Panoply provides its users with an integrated data warehouse solution, allowing for seamless storage and analytics, while Stitch focuses on data integration and pipelines, requiring users to store their data in separate data warehouses or cloud storage solutions.
In Summary, Panoply and Stitch differ in their support for data sources, data transformation capabilities, real-time processing, scalability, cost structure, and data storage solutions.

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Detailed Comparison

Stitch
Stitch
Panoply
Panoply

Stitch is a simple, powerful ETL service built for software developers. Stitch evolved out of RJMetrics, a widely used business intelligence platform. When RJMetrics was acquired by Magento in 2016, Stitch was launched as its own company.

It is the data warehouse built for analysts. Our data management platform automates all three key aspects of the data stack: data collection, management, and query optimization.

Connect to your ecosystem of data sources - UI allows you to configure your data pipeline in a way that balances data freshness with cost and production database load;Replication frequency - Choose full or incremental loads, and determine how often you want them to run - from every minute, to once every 24 hours; Data selection - Configure exactly what data gets replicated by selecting the tables, fields, collections, and endpoints you want in your warehouse;API - With the Stitch API, you're free to replicate data from any source. Its REST API supports JSON or Transit, and recognizes your schema based on the data you send.;Usage dashboard - Access our simple UI to check usage data like the number of rows synced by data source, and how you're pacing toward your monthly row limit;Email alerts - Receive immediate notifications when Stitch encounters issues like expired credentials, integration updates, or warehouse errors preventing loads;Warehouse views - By using the freshness data provided by Stitch, you can build a simple audit table to track replication frequency;Scalable - Highly Scalable Stitch handles all data volumes with no data caps, allowing you to grow without the possibility of an ETL failure;Transform nested JSON - Stitch provides automatic detection and normalization of nested document structures into relational schemas;Complete historical data - On your first sync, Stitch replicates all available historical data from your database and SaaS tools. No database dump necessary.
Data warehouse; Business Intelligence;Optimized Query Engine
Statistics
Stacks
150
Stacks
9
Followers
150
Followers
17
Votes
12
Votes
0
Pros & Cons
Pros
  • 8
    3 minutes to set up
  • 4
    Super simple, great support
No community feedback yet
Integrations
Stripe
Stripe
Twilio SendGrid
Twilio SendGrid
Zendesk
Zendesk
MongoDB
MongoDB
Marketo
Marketo
Recurly
Recurly
GitLab
GitLab
Zapier
Zapier
FreshDesk
FreshDesk
Harvest
Harvest
HubSpot
HubSpot
MySQL
MySQL
Metabase
Metabase
Google Analytics
Google Analytics
Airbrake
Airbrake
Braintree
Braintree
Amazon S3
Amazon S3
QuickBooks
QuickBooks
Tableau
Tableau
PostgreSQL
PostgreSQL

What are some alternatives to Stitch, Panoply?

Google BigQuery

Google BigQuery

Run super-fast, SQL-like queries against terabytes of data in seconds, using the processing power of Google's infrastructure. Load data with ease. Bulk load your data using Google Cloud Storage or stream it in. Easy access. Access BigQuery by using a browser tool, a command-line tool, or by making calls to the BigQuery REST API with client libraries such as Java, PHP or Python.

Amazon Redshift

Amazon Redshift

It is optimized for data sets ranging from a few hundred gigabytes to a petabyte or more and costs less than $1,000 per terabyte per year, a tenth the cost of most traditional data warehousing solutions.

Qubole

Qubole

Qubole is a cloud based service that makes big data easy for analysts and data engineers.

Amazon EMR

Amazon EMR

It is used in a variety of applications, including log analysis, data warehousing, machine learning, financial analysis, scientific simulation, and bioinformatics.

Altiscale

Altiscale

we run Apache Hadoop for you. We not only deploy Hadoop, we monitor, manage, fix, and update it for you. Then we take it a step further: We monitor your jobs, notify you when something’s wrong with them, and can help with tuning.

Snowflake

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.

Azure Synapse

Azure Synapse

It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.

Dremio

Dremio

Dremio—the data lake engine, operationalizes your data lake storage and speeds your analytics processes with a high-performance and high-efficiency query engine while also democratizing data access for data scientists and analysts.

Cloudera Enterprise

Cloudera Enterprise

Cloudera Enterprise includes CDH, the world’s most popular open source Hadoop-based platform, as well as advanced system management and data management tools plus dedicated support and community advocacy from our world-class team of Hadoop developers and experts.

Airbyte

Airbyte

It is an open-source data integration platform that syncs data from applications, APIs & databases to data warehouses lakes & DBs.

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