Most businesses have data stored in a variety of locations, from in-house databases to SaaS platforms. To get a full picture of their finances and operations, they pull data from all those sources into a data warehouse or data lake and run analytics against it. But they don't want to build and maintain their own data pipelines.
Fortunately, it’s not necessary to code everything in-house. Here's an comparison of three such tools, head to head.
About AWS Glue
Amazon Web Services (AWS) has a host of tools for working with data in the cloud. Glue focuses on ETL. It's one of two AWS tools for moving data from sources to analytics destinations; the other is AWS Data Pipeline, which is more focused on data transfer.
Stitch and Talend partner with AWS. While this page details our products that have some overlapping functionality and the differences between them, we're more complementary than we are competitive. AWS offers lots of products beyond what's mentioned on this page, and we have thousands of customers who successfully use our solutions together.
About Google Cloud Dataprep
Google Cloud Dataprep is a data service for exploring, cleaning, and preparing structured and unstructured data. It's one of several Google data analytics services, including:
- BigQuery, a cloud data warehouse
- Google Data Studio, a relatively simple platform for reporting and visualization
- Google Cloud Datalab, a more robust analytics tool that lets data professionals explore, analyze, transform, and visualize data and build machine learning models
- Google Cloud Dataflow, a platform for ingesting and processing real-time data
- Google Cloud Data Fusion, a cloud-native data integration service
Stitch Data Loader is a cloud-based platform for ETL — extract, transform, and load. More than 3,000 companies use Stitch to move billions of records every day from SaaS applications and databases into data warehouses and data lakes, where it can be analyzed with BI tools. Stitch is a Talend company and is part of the Talend Data Fabric.
|Focus||ETL, data catalog||Data transformation||Data ingestion, ELT|
|Database replication||Full table; incremental via change data capture through AWS Database Migration Service (DMS)||None||Full table; incremental via change data capture or SELECT/replication keys|
|SaaS sources||None||None||More than 100|
|Ability for customers to add new data sources||Developers can write custom Scala or Python code and import custom libraries and Jar files into Glue ETL jobs to access data sources not natively supported by AWS Glue.||No||Yes|
|Connects to data warehouses? Data lakes?||Yes / Yes||Yes / Yes||Yes / Yes|
|G2 customer satisfaction||4.1/5||4.1/5||4.8/5|
|Purchase process||Options for self-service and talking with sales||Self-service||Options for self-service or talking with sales. Also available from the AWS store.|
|Compliance, governance, and security certifications||HIPAA, GDPR||HIPAA||HIPAA, GDPR, SOC 2|
|Data sharing||Yes, within AWS||Yes||Yes, through Talend Data Fabric|
|Vendor lock-in||Month to month||Month to month or annual contracts. Open source integrations|
|Developer tools||REST API for creating job groups||Import API, Stitch Connect API for integrating Stitch with other platforms, Singer open source project|
Let's dive into some of the details of each platform.
AWS Glue provides 16 built-in preload transformations that let ETL jobs modify data to match the target schema. Glue generates Python code for ETL jobs that developers can modify to create more complex transformations, or they can use code written outside of Glue.
Google Cloud Dataprep
Cloud Dataprep's main purpose is to let data analysts explore, clean, and prepare data for analysis. It provides tools to format, filter, and run macros against data. It uses a visual interface to cleanse and enrich multiple data sources before loading them to a Google Cloud Storage data lake or BigQuery data warehouse.
Stitch is an ELT product. Within the pipeline, Stitch does only transformations that are required for compatibility with the destination, such as translating data types or denesting data when relevant. Stitch is part of Talend, which also provides tools for transforming data either within the data warehouse or via external processing engines such as Spark and MapReduce. Transformations can be defined in SQL, Python, Java, or via graphical user interface.
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Connectors: Data sources and destinations
Each of these tools supports a variety of data sources and destinations.
AWS Glue supports AWS data sources — Amazon Redshift, Amazon S3, Amazon RDS, and Amazon DynamoDB — and AWS destinations, as well as various databases via JDBC. Glue can also serve as an orchestration tool, so developers can write code that connects to other sources, processes the data, then writes it out to the data target.
Google Cloud Dataprep
Cloud Dataprep is a whitelabeled, managed version of Trifacta Wrangler. It can read data from Google Cloud Storage and BigQuery, and can import files. Cloud Dataprep doesn't support any SaaS data sources. It can write data to Google Cloud Storage or BigQuery.
Stitch supports more than 100 database and SaaS integrations as data sources, and eight data warehouse and data lake destinations. Customers can contract with Stitch to build new sources, and anyone can add a new source to Stitch by developing it according to the standards laid out in Singer, an open source toolkit for writing scripts that move data. Singer integrations can be run independently, regardless of whether the user is a Stitch customer. Running Singer integrations on Stitch’s platform allows users to take advantage of Stitch's monitoring, scheduling, credential management, and autoscaling features.
Support, documentation, and training
Data integration tools can be complex, so vendors offer several ways to help their customers. Online documentation is the first resource users often turn to, and support teams can answer questions that aren't covered in the docs. Vendors of the more complicated tools may also offer training services.
AWS provides several levels of support. Free Basic support provides access to support forums. Develop support adds client-side diagnostic tools and guidance on how to use AWS products, features, and services together. Business and Enterprise plans add additional options. Documentation is comprehensive. Both digital training and classroom training services are available.
Google Cloud Dataprep
Google provides several support plans for Google Cloud Platform, which Cloud Dataprep is part of. Documentation is comprehensive. Google offers both digital and in-person training.
Stitch provides in-app chat support to all customers, and phone support is available for Enterprise customers. Support SLAs are available. Documentation is comprehensive and is open source — anyone can contribute additions and improvements or repurpose the content. Stitch does not provide training services.
AWS Glue ETL jobs are billed at an hourly rate based on data processing units (DPU), which map to performance of the serverless infrastructure on which Glue runs. For the AWS Glue Data Catalog, users pay a monthly fee for storing and accessing Data Catalog the metadata. The first million objects stored are free, and the first million accesses are free. A development endpoint provisioned to interactively develop ETL code is billed per second.
Google Cloud Dataprep
Cloud Dataprep jobs are executed by Cloud Dataflow workers, which are priced per second for CPU, memory, and storage resources.
Stitch has pricing that scales to fit a wide range of budgets and company sizes. All new users get an unlimited 14-day trial. Standard plans range from $100 to $1,250 per month depending on scale, with discounts for paying annually. Enterprise plans for larger organizations and mission-critical use cases can include custom features, data volumes, and service levels, and are priced individually.
Get started now
Which tool is best overall? That's something every organization has to decide based on its unique requirements, but we can help you get started. Sign up now for a free trial of Stitch.