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 two such tools, head to head.

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 and Talend partner with Google. While this page details our products that have some overlapping functionality and the differences between them, we're more complementary than we are competitive. Google offers lots of products beyond those mentioned here, and we have thousands of customers who successfully use our solutions together.

About Google Cloud Dataflow

Google Cloud Dataflow lets users ingest, process, and analyze fluctuating volumes of real-time 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 Dataprep, a data service for exploring, cleaning, and preparing structured and unstructured data
Google Cloud Data Fusion, a cloud-native data integration service

About Stitch

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	Data transformation	Stream and batch processing	Data ingestion, ELT
Database replication	None	Full table; incremental replication via custom SELECT statements	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	No	Yes	Yes
Connects to data warehouses? Data lakes?	Yes / Yes	Yes / Yes	Yes / Yes
Transparent pricing	Yes	Yes	Yes
G2 customer satisfaction	4.1/5	4.1/5	4.8/5
Support SLAs	Yes	Yes	Available
Purchase process	Self-service	Self-service	Options for self-service or talking with sales. Also available from the AWS store.
Compliance, governance, and security certifications	HIPAA	HIPAA	HIPAA, GDPR, SOC 2
Data sharing	Yes	Yes	Yes, through Talend Data Fabric
Vendor lock-in	Month to month	Month to month	Month to month or annual contracts. Open source integrations
Developer tools	REST API for creating job groups	Cloud Dataflow REST API, SDKs for Java and Python	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.

Transformations

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.

Google Cloud Dataflow

Cloud Dataflow provides a serverless architecture that can shard and process large batch datasets or high-volume data streams. The software supports any kind of transformation via Java and Python APIs with the Apache Beam SDK.

Stitch

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.

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.

Google Cloud Dataflow

Cloud Dataflow supports both batch and streaming ingestion. For batch, it can access both GCP-hosted and on-premises databases. For streaming, it uses PubSub. Cloud Dataflow doesn't support any SaaS data sources. It can write data to Google Cloud Storage or BigQuery.

Stitch

Stitch supports more than 100 database and SaaS integrationsas 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.

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.

Google Cloud Dataflow

Google provides several support plans for Google Cloud Platform, which Cloud Dataflow is part of. Documentation is comprehensive. Google offers both digital and in-person training.

Stitch

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.

Pricing

Google Cloud Dataprep

Cloud Dataprep jobs are executed by Cloud Dataflow workers, which are priced per second for CPU, memory, and storage resources.

Google Cloud Dataflow

Cloud Dataflow is priced per second for CPU, memory, and storage resources.

Stitch

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 better 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.

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