Businesses today generate massive amounts of data. This data is scattered across different systems used by the business – Cloud Applications, Database, SDKs, etc. To gain valuable insight from this data deep analysis is required. As a first step, companies would want to move this data to a single location for easy access and seamless analysis. Data pipeline tools facilitate exactly this.
Before we dive into the details, here is a snapshot of what this post covers:
- What is a Data Pipeline Tool?
- Batch vs Real-time Data Pipeline Tools
- Open source vs Proprietary Tools
- On-premise vs Cloud-native Tools
- How to choose the right Data Pipeline tool
- Exploring a No-Code Data Pipeline Solution
So, What is a Data Pipeline Tool?
Dealing with data can be tricky. To be able to get real insights from data, you would need to:
- Extract data from multiple data sources that matter to you.
- Clean, transform and enrich this data to make it analysis-ready.
- Load this data to a single source of truth – more often a data lake or data warehouse.
Each of these steps can be done manually. Alternatively, each of these steps can be automated using separate software tools too.
However, during the process, there are many things can break. The code can throw errors, data can go missing, incorrect/inconsistent data can be loaded and so on. The bottlenecks and blockers are limitless.
Often, a data pipeline tool is used to automate this process end-to-end in an efficient, reliable and secure manner. data pipeline software guarantee consistent and effortless migration from various data sources to a destination – often a data lake or data warehouse.
Types of Data Pipeline Tools
Depending on the purpose, there are different types of data pipeline tools available. The popular types are as follows –
1. Batch vs Real-time:
Batch data pipeline tools allow you to move data, usually a very large volume, at a regular interval or batches. This comes at the expense of real-time operation. More often than not, these type of tools is used for on-premise data sources or in cases where real-time processing can constrain the regular business operation due to limited resources. Some of the famous batch data pipeline tools are as follows:
The Real-time ETL tools are optimized to process data in real-time. Hence, these are perfect if you are looking to have analysis ready at your fingertips day in-day out. These tools also work well if you are looking to extract data from a streaming source, e.g. the data from user interactions that happen on your website/mobile application. Some of the famous real-time data pipeline tools are as follows:
2. Open source vs Proprietary:
Open source means the underlying technology of the tool is publicly available and therefore need customization for every use case. Being open-source this type of data pipeline tools are free or charge a very nominal price. This also means you would need to have the required expertise to develop and extend its functionality as per need. Some of the known open-source data pipeline tools are:
The proprietary data pipeline tools are tailored as per specific business use, therefore require no customization and expertise for maintenance on the user’s part. They mostly work out of the box. Here are some of the best proprietary data pipeline tools that you should explore:
3. On-premises vs Cloud-native:
Previously, businesses had all their data stored in on-premise systems. Hence, the data lake/data warehouse also had to be set up on-premise. These tools clearly offer better security as they are deployed on the customer’s local infrastructure. Some of the platforms that support on-premise data pipelines are:
Cloud-native data pipeline tools allow transfer and processing of cloud-based data to data warehouses hosted in the cloud. Here the vendor hosts the data pipeline allowing the customer to save resources on infrastructure. Cloud-based service providers put a heavy focus on security as well. The platforms that support cloud data pipelines are as follows:
The choice of a data pipeline that would suit you is based on many factors unique to your business. Let us look at some criteria that might help you further narrow down your choice of data pipeline Tool.
How to choose the right Data Pipeline tool?
With so many data pipeline tools available in the market there are a couple of factors one should consider while selecting the best-suited one as per the need.
- Easy Data Replication – The tool you choose should allow you to intuitively build a pipeline and set up your infrastructure in minimal time.
- Maintenance Overhead – The tool should have minimal maintenance overhead and should work pretty much out of the box.
- Data Sources Supported – It should allow you to connect to numerous and various data sources. You should also consider support for those sources you may need in the future.
- Data Reliability – It should transfer and load data without error or dropped packet.
- Realtime Data Availability – Depending on your use case, decide if you need data real-time or in batches will be just fine.
- Customer Support – Any issue while using the tool should be solved quickly and for that choose the one offering most responsive and knowledgeable customer sources
Hevo – A Modern Data Pipeline Platform
Hevo lets you bring your data from any source to your data lake or data warehouse in real-time – without having to write any code. Watch a quick 5 min video on how Hevo can help:
Here is why Hevo might be the right data pipeline platform for your needs:
- 100s of Data Sources: Hevo can natively integrate with many different data sources – Databases, Cloud Application, SDKs, FTP/SFTP and more to bring data to your preferred destination.
- Easy setup: Your data replication projects can come to life in a matter of few minutes with Hevo. Hevo’s intuitive user interface makes it super easy to build data pipelines and move data in a jiffy.
- Realtime Data Availability – Hevo’ real-time streaming architecture ensures that the data is streamed in near real-time from source to destination.
- Zero Data Loss – Hevo is fault-tolerant. It ensures that all your data is moved accurately, in an error-free fashion with no data loss.
- Automatic Schema Detection and Evolution – Hevo’s AI-powered algorithms automatically detect the schema of the incoming data and map it to the warehouse schema. Incase the schema changes in the future, Hevo automatically handles this removing any manual intervention from your end.
- Advanced Features – Hevo comes with a python-based interface where you can clean, transform and enrich your data. In addition, Hevo lets you model your data by building joins and aggregates within the warehouse. This will ensure your data is always analysis-ready.
What more? Sign up for a 14-day free trial here to seamlessly build your data pipelines.