Most modern enterprises use a multitude of cloud-based apps. For example, the sales team may use Salesforce to capture new leads, the marketing department may use HubSpot to manage campaigns and the finance department may use QuickBooks to track expenses.

Using so many apps and tools causes data to become disparate and creates data silos. This can make it difficult to perform timely data analysis and get detailed business insights. Manually consolidating the data, processing it without any errors and building your pipeline can be time-consuming, costly and laborious. 

Data pipeline tools solve this problem. They consolidate raw data from various sources into a central destination (e.g., data lake, data warehouse) and make that data available for business analysis. 

In this article, we’ll look at the types of data pipelines and share six options for you to consider.

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Data pipelines: How do they function?

Data pipelines are also called data connectors and consist of three parts:

• Data source: Data sources can be internal databases like PostgreSQL, external data sources like Qualtrics or cloud applications like Shopify.
  
  
• Destinations: Destinations are locations where data is stored once it’s extracted from a source. They’re also called data lakes or data warehouses. Examples include Snowflake, RedBricks and Google BigQuery.
  
  
• Data transformation: Data transformation allows you to structure and normalize data so that it’s ready for interpretation and analysis. Transformation can be done through platforms like data build tool (dbt), Matillion, EasyMorph and Amazon Web Services (AWS) Glue.
  
  Examples of data transformation include data deduplication, standardization, adding or copying data, summarizing data, deleting fields or records, filtering and enriching or converting data.

Once data is transformed, you can use business intelligence (BI) tools like Tableau or Looker to gain valuable insights.

This process is also called Extract, Load, Transform (ELT), where data is transferred from source to destination and then transformed by data analysts and engineers for comprehensive business understanding. Many organizations also adopt the Extract, Transform, Load approach (ETL), where data is first transformed and then loaded. 

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Though both have benefits for various use cases, most businesses today are adopting the ELT architecture because of its flexibility, scalability and affordability. 

Refer to this post to learn more about how ELT differs from ETL.

Types of data pipelines 

There are three types of data pipelines based on how frequently you want to transfer data and whether you want the pipelines on-premise or in the cloud. 

Here’s a look at each of them.

Real-time vs. batch data pipeline tools

Real-time: Real-time data pipelines, also called streaming data pipelines help businesses capture and transfer data instantly, on-the-fly. These are useful for businesses like fleet management services where timing (to receive the data) is the most crucial factor. 

Batch: Batch processing data pipelines collect and process data in intervals based on a regular fixed schedule. Processing data in batches can take a lot of time, so this method is suitable for businesses that don’t need to work with real-time analytics. 

Open source vs. proprietary data pipeline tools

Open source: Open source pipelines are an inexpensive alternative to a cloud-based data pipeline tool. These tools are cheaper than commercial products, but you need technical and coding knowledge to use them. Because they're available to the public for no cost, other users can modify them.

Proprietary: Proprietary data pipelines are built for specific use cases and hence the end-user doesn’t need to maintain the pipelines or have any technical knowledge to use them. They are prepackaged and have out-of-the-box features. 

Cloud-based vs. self-hosted data pipeline tools

Cloud-based: Cloud-based data pipelines allow for easy integration between different systems, such as customer relationship management (CRM), enterprise resource planning (ERP) and BI tools. They also provide a central location in the cloud where all data resides, making it easier for users to access data from any system and any place. Businesses don’t have to invest in resources or physical infrastructure to adopt cloud pipelines. 

Self-hosted: Self-hosted data pipelines are hosted on-premise on the user’s local servers. Though the user has to maintain the pipelines and handle updates, they provide better security since all the data is with the customer and not in the cloud. 

Top six data pipeline tools 

Here we’ll cover the six best picks for data pipeline tools, starting with our own solution Fivetran. 

1. Fivetran 

At Fivetran, we believe that leveraging your data for insights requires a robust, agile and flexible data integration infrastructure that doesn’t take months to build. 

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Fivetran is an easy cloud-based ELT data pipeline that lets you centralize all your data from multiple sources in your data warehouse within a few minutes. 

Our zero-maintenance pipeline solution comes with pre-built and pre-configured data connectors that support 150+ data sources like various cloud services, databases and applications. 

All our connectors are fully managed, so you get 99.9 percent uptime. Plus, whenever vendors make changes, Fivetran automatically updates the schema by adding new tables or by adding and removing columns. It also keeps up with API changes, so you always get the freshest data for analytics.

Our data pipelines are fault-tolerant and auto-recovering whenever there’s a failure. And we ensure that your data assets are normalized before they are ready for analysis. 

Our Metadata API governs data movement and provides enhanced visibility into where the data came from, who accessed it and what changes have occurred in the pipeline. 

We support data destinations like Snowflake, databricks, Google Cloud, Azure, Amazon RedShift and Amazon S3. We recommend Fivetran for marketing, sales and support, finance and ops teams.

Online reviewers love that they can significantly reduce the overhead of maintaining and monitoring data ingestion connections and feeds. Users also share that it takes hours off from developers’ time so they don’t have to go through detailed documentation or testing integrations and that no backend is required to set up the pipelines. 

Learn more about our pricing plans here. 

Case study: Fivetran & ASICS

After migrating from SAP to Salesforce Marketing Cloud, ASICS sought a less resource-intensive data pipeline tool. 

Without Fivetran, it would have taken them six months to build the pipeline internally and migrate data from the SAP stack to Salesforce. However, with Fivetran as its data pipeline solution and Snowflake as its destination, they built a data pipeline in six days. 

Our modern data architecture has allowed ASICS Digital to:

• Improve their marketing technology capabilities
• Centralize NetSuite data
• Implement machine learning
• Build a comprehensive view of their customer base without hiring additional data engineers.

Read the entire case study here. 

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2. Stitch Data

Stitch is a data pipeline tool that lets you connect data from databases like MySQL and SaaS apps like Salesforce and Zendesk — and replicates them in your preferred cloud data warehouses, all without coding.  

You can also schedule the frequency for your replication (i.e., replicate data every eight hours) so that your data is available for analysis whenever you need it. 

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Key features:

• Stitch Data is SOC2, PCI, GDPR and HIPAA compliant for enhanced security.
• It offers connections to 100+ SaaS apps, so getting all your data in a central spot becomes hassle-free. 
• Support for cloud destinations like Microsoft Azure Synapse Analytics, Snowflake, Amazon, Redshift and Google BigQuery.  
• Simple-to-use interface that anyone in your team can get started within a few minutes.
• Can handle critical workloads and comes with multiple redundant safeguards that keep data safe in case of any outages. 

Plans start at $100 per month.

3. AWS Data Pipeline

With AWS Data Pipeline, businesses can securely process and transfer data between AWS compute and storage services and on-premise data sources at fixed intervals. 

AWS Data Pipeline lets you easily access data from where it’s stored, process it at scale and transfer results to AWS services like Amazon EMR, Amazon S3, Amazon DynamoDB and more. 

Key features: 

• Drag-and-drop console to quickly create pipelines.
• Flexible design, so processing a million files is as simple as processing a single file.
• No need to write logic or code as common preconditions are available by default. 
• Collection of pipeline templates so you don’t have to do anything from scratch and use templates for complex cases like running periodic SQL queries. 
• Can create sophisticated and fault-tolerant data processing workflows.
• No need to manage inter-task dependencies or retry timeouts for individual tasks. 
• Automatic activity retrial if failures exist in activity logic or data sources. 
• Automatic failure notifications via Amazon Simple Notification Service (Amazon SNS).

Pricing for AWS Data Pipeline is based on usage.

4. Gravity Data

Gravity Data allows data analysts, engineers and data scientists to build data pipelines (within five minutes) without writing any code or depending on DevOps or IT teams. 

You can add your sources, destinations and integrations from one dashboard and save time juggling between different interfaces. 

Key features: 

• Can connect data from any source like APIs, databases and files with 110+ data connectors. 
• High-throughput data pipelines that let you access both historical and streaming data. 
• Real-time tracking of data pipeline progress.
• Read and write from various file formats like CSV, TSV, JSON and Parquet.
• Debugging functionality that diagnoses and resolves errors. 
• Automatic updates in Slack, Teams and Webhooks.
• Ability to create syncs and jobs that let you create workflows.
• Cron expression for advanced scheduling like setting whitelist hours.
• Encryption at rest, endpoint safety, pen testing and anomalous behavior tracking.  

Gravity Data comes with a 15-day free trial and is free for 1 million rows. Paid plans start at $270 per month for 20 million rows.

5. Hevo Data

Hevo is a no-code data pipeline and data integration platform. It allows you to ingest data from 150+ data sources into a warehouse (e.g., Amazon Web Services or Oracle) and transforms that data for analytics in your preferred BI platform.

Key features:

• Python-based drag-and-drop transformations to prepare data for analysis
• Ability to create SQL-based models and transform data for business insights. 
• Agile data replication process — you can change settings for data loading even after creating the pipeline. 
• Email and Slack notifications that give you updates on pipeline status.
• Graphs and UI indications that let you see latency and speed of data ingestion, success or failure of replication stages, event failures and more.  

Hevo offers a free plan that includes 50 data connectors and up to million row inserts or updates. Paid plans start at $239 per month for 150 data connectors and up to five million row inserts or updates.

6. CData Software

CData Software provides simple data connectivity that lets you integrate all your data across your tech stack in real-time. You can securely connect your data from any tool or software from on-premise or in the cloud. 

CData Software has 200+ connectors that let you connect your ETL, BI and custom apps with any Big Data source, NoSQL or SaaS apps.  

Key features:

• Effortless data integration to every CRM, ERP, automation, marketing and accounting system.
• Ability to ingest real-time data to Power BI, Sisense, DataStudio, Spotfire and Tableau through drivers and adapters.
• Self-serve integration features so citizen analysts can connect their data without any help from IT.
• Integrate with ETL and data warehousing platforms like Amazon Redshift, Google BigQuery, Oracle Data Integrator, Amazon S3, Snowflake, etc. 
• Enterprise-class reliable and scalable design with a powerful SQL engine that speeds up data movement and processing.
• Secure SSL/TLS encryption.

CData Software offers five products depending on the features you need to build your data pipeline tool. Each of these products has different pricing plans.

Try Fivetran as your data pipeline tool 

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Organizations use 110 cloud apps on average, which is why businesses are generating huge volumes of data. Data pipelines are the way to get insights and meaning out of this data. But how do you choose the right data pipeline for your business?

Every data pipeline tool has its key features, limitations, pricing options and use cases. So when you’re looking for a tool, look for features that match your business needs and use cases. 

Ask these questions to get more clarity and simplify decision-making: 

• Is it out-of-the-box or will you require some maintenance to keep the tool running?
• Do you need real-time data syncing?
• What data sources does the tool support? 
• How much time does it take for the tool to transfer data from source to destination without any errors? 
• What are the reviews saying about customer support? 
• What are the pricing options? 

Fivetran is a cloud-based platform that allows businesses to easily build, deploy, manage, monitor and analyze their data pipelines. With Fivetran, users can quickly set up and run data pipelines in minutes. To test our features, sign up for a 14-day free trial.