Google Cloud Data Fusion vs. Google Cloud Dataflow vs. Stitch
ETL software comparison
ETL software comparison
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.
Google Cloud Data Fusion is a cloud-native data integration service. It's one of several Google data analytics services, including:
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.
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:
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.
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 integration | Stream and batch processing | Data ingestion, ELT | |||||||||||
Database replication | Full table; incremental replication via custom SELECT statements | 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 | Yes | Yes | Yes | |||||||||||
Connects to data warehouses? Data lakes? | Yes / Yes | Yes / Yes | Yes / Yes | |||||||||||
Transparent pricing | Yes | Yes | Yes | |||||||||||
G2 customer satisfaction | Not Rated | 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. Cloud Data Fusion is powered by the open source project CDAP | Month to month | Month to month or annual contracts. Open source integrations | |||||||||||
Developer tools | REST API to manage Cloud Data Fusion instances | 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.
Cloud Data Fusion supports simple preload transformations — validating, formatting, and encrypting or decrypting data, among other operations — created in a graphical user interface.
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 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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Each of these tools supports a variety of data sources and destinations.
Cloud Data Fusion is a beta service on Google Cloud Platform. The platform supports almost 20 file and database sources and more than 20 destinations, including databases, file formats, and real-time resources. Cloud Data Fusion doesn't support any SaaS data sources.
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 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.
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 provides several support plans for Google Cloud Platform, which Cloud Data Fusion is part of. Documentation is comprehensive. Google offers both digital and in-person training.
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 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.
Cloud Data Fusion is priced differently for development and execution. Development is priced per instance per hour at two different rates, for Basic and Enterprise editions. Execution runs at Google Cloud Dataproc rates.
Cloud Dataflow is 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.
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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