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 Improvado

Improvado is a cloud-based ETL platform aimed primarily at marketing companies.

About Segment

Segment has a different focus than most ETL tools — it's designed to collect and connect customer data from multiple marketing, analytics, and data warehousing tools and unify it into customer profiles. It's not primarily an ETL tool, but it does include connectivity to some SaaS data sources and data warehouse destinations.

In Segment, an event is a set of actions that represents a step in the funnel, such as user invited or signed up or order completed. Users can define events that make sense for their business use cases, based on key metrics that provide business value, and create tracking plans to document the events and properties they intend to collect across Segment sources.

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.

Improvado LogoSegment LogoStitch Logo
Focus Data ingestion, marketing dashboardEvent tracking, data ingestion, ELTData ingestion, ELT
Database replication No database data sourcesNo database data sourcesFull table; incremental via change data capture or SELECT/replication keys
SaaS sources About 80About 35More than 100
Ability for customers to add new data sourcesNoFor events but not cloud app sources (see explanation below)Yes
Connects to data warehouses? Data lakes?Yes / YesYes / NoYes / Yes
Transparent pricingNoYesYes
G2 customer satisfactionHelpNot Rated4.6/54.8/5
Support SLAsUnknownAvailableAvailable
Purchase process Requires a conversation with salesOptions for self-service and talking with salesOptions for self-service or talking with sales. Also available from the AWS store.
Compliance, governance, and security certificationsNoneGDPRHIPAA, GDPR, SOC 2
Data sharingNoNoYes, through Talend Data Fabric
Vendor lock-inUnknownMonth to month or annual contracts. The company maintains several open source projects.Month to month or annual contracts. Open source integrations
Developer toolsREST APIJavaScript library, mobile SDKs, server-side libraries, HTTP Tracking API, Pixel Tracking API, Objects API, Objects Bulk APIImport 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

Improvado

Improvado provides preload transformations on data moved through the Improvado UI. Improvado transforms data into a format that they believe to be better for users, but it doesn't support user-configured transformations. Improvado also lets customers move raw data to a destination by writing code that calls their API.

Segment

To the extent that it performs ETL operations, Segment focuses on the E and L, extraction and loading. It extracts raw data from sources and loads it into destinations without allowing users to define their own transformations — though Segment itself transforms events and objects to conform to its standard as it sends them between different tools, including to the data warehouse.

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.

Improvado

Improvado supports about 80 integrations to SaaS platforms. Several other data sources are "available by request only." Improvado supports Amazon Redshift and Google BigQuery data warehouses; Amazon S3 and Google Cloud Storage data lakes; and PostgreSQL, MySQL, Microsoft SQL Server, and Postgres Plus database destinations. Customers can request that the company build a new data source or destination, but no one outside of the company can build new ones or make improvements to existing ones.

Segment

<p>Segment offers integrations for several different kinds of sources:</p> <li>It tracks and sends events between more than 250 supported tools.</li> <li>It replicates data from about 35 cloud app sources that are common among ETL tools.</li> <br> <p>To understand the difference between the events and SaaS data sources, take the example of Salesforce, which is one of a handful of integrations supported in both categories. Event tracking would enable updates to Salesforce leads and contacts based things those users did in a separate system, like a mobile app.</p> <p>If you want to replicate all of the data in your Salesforce instance to your data warehouse, including information entered by your sales team, that’s only possible with a cloud app source.</p> <p>Customers can use Segment's developer tools to track new event sources, but no one outside of the Segment team can build new cloud app sources.</p> <p>Segment supports six destinations:</p> <li>Amazon Redshift</li> <li>Google BigQuery</li> <li>Snowflake</li> <li>Azure SQL Data Warehouse</li> <li>Postgres</li> <li>IBM Db2</li>

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.

Improvado

Improvado provides support through Intercom online chat and via email. Documentation is provided in the form of how-to articles. The company doesn't provide training services.

Segment

Segment provides support through a ticketing system. Documentation is comprehensive. Segment does not provide training services.

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

Improvado

Improvado doesn't disclose pricing, and has no free trial period.

Segment

Segment provides a 14-day free trial, and has a free Developer tier. Team accounts start at $120 per month. Pricing is based in part on the volume of monthly tracked users in data sources. Business plans for larger organizations are priced individually.

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.

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