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

Azure Synapse vs Stitch

OverviewComparisonAlternatives

Overview

Stitch
Stitch
Stacks150
Followers150
Votes12
Azure Synapse
Azure Synapse
Stacks104
Followers230
Votes10

Stitch vs Azure Synapse: What are the differences?

Stitch: All your data. In your data warehouse. In minutes. 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; Azure Synapse: Analytics service that brings together enterprise data warehousing and Big Data analytics. 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.

Stitch belongs to "Big Data as a Service" category of the tech stack, while Azure Synapse can be primarily classified under "Big Data Tools".

Some of the features offered by Stitch are:

  • 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

On the other hand, Azure Synapse provides the following key features:

  • Complete T-SQL based analytics – Generally Available
  • Deeply integrated Apache Spark
  • Hybrid data integration

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Detailed Comparison

Stitch
Stitch
Azure Synapse
Azure Synapse

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 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.

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.
Complete T-SQL based analytics – Generally Available; Deeply integrated Apache Spark; Hybrid data integration; Unified user experience
Statistics
Stacks
150
Stacks
104
Followers
150
Followers
230
Votes
12
Votes
10
Pros & Cons
Pros
  • 8
    3 minutes to set up
  • 4
    Super simple, great support
Pros
  • 4
    ETL
  • 3
    Security
  • 2
    Serverless
  • 1
    Doesn't support cross database query
Cons
  • 1
    Dictionary Size Limitation - CCI
  • 1
    Concurrency
Integrations
Stripe
Stripe
Twilio SendGrid
Twilio SendGrid
Zendesk
Zendesk
MongoDB
MongoDB
Marketo
Marketo
Recurly
Recurly
GitLab
GitLab
Zapier
Zapier
FreshDesk
FreshDesk
Harvest
Harvest
No integrations available

What are some alternatives to Stitch, Azure Synapse?

Metabase

Metabase

It is an easy way to generate charts and dashboards, ask simple ad hoc queries without using SQL, and see detailed information about rows in your Database. You can set it up in under 5 minutes, and then give yourself and others a place to ask simple questions and understand the data your application is generating.

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.

Apache Spark

Apache Spark

Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.

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.

Presto

Presto

Distributed SQL Query Engine for Big Data

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.

Amazon Athena

Amazon Athena

Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.

Superset

Superset

Superset's main goal is to make it easy to slice, dice and visualize data. It empowers users to perform analytics at the speed of thought.

Apache Flink

Apache Flink

Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala.

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