A data pipeline is a process of analyzing data that advances from one system to the other. As the volume and variety of data are increased in an organization, there is a requirement for a more efficient data pipeline. Businesses are heavily dependant on data and regularly analyze it to uncover critical information. Just as these businesses have expanded, so have the data pipeline tools.
In this article, we will briefly understand the best data pipeline tools of 2023. We will also explore the features and aspects of these data pipeline tools for your business.
List of 8 Best Data Pipeline Tools – 2023:
Keboola is a SaaS data operations platform, as it looks after the complete data pipeline operational cycle. It provides solutions and products to supervise over ETL (extract-transform-load) as well as orchestrate and monitor data in an organization. One of its key features allows businesses to customize the solution as per their requirements.
Keboola is an ideal solution for businesses as well as startups. Its solutions are suitable for businesses of all sizes and functions, due to their customizable solutions.
In 2020, Compology which is a data-driven Internet-of-Things company began its collaboration with Keboola. Before this Compology worked with Stitch and an open-source database named PostgreSQL.
As the company expanded, they began facing limitations with Stitch as they had multiple departments to cater to and Stitch had constraints supporting them. Hence, they went ahead with Keboola as they offered unlimited data sources without the new charge per connector.
That was the major differentiator between Keboola and other solutions. According to Clarice Robenalt, Analytics Engineer at Compology, “Keboola supports continuous innovation in a way that our previous setup did not. It’s really exciting to be able to have a new idea in the morning and turn around a new report within hours, if not less.”
She stated that Keboola didn’t just help Compology grow, but also widened her opportunities in her career as it is a user-friendly platform.
Key Features for business:
- Keboola provides complete solutions for businesses to help manage their data.
- It is a one-stop-shop for data extraction to data modeling to data storage.
- It provides control over each step in the ETL process that businesses could use to develop their opportunities.
- It allows a leaner data team to cover more tasks as the responsibilities can be handled by one or two people rather than assigning an entire team to complete it.
- As mentioned, one of its key features is to provide customizable solutions, by allowing businesses to design the workflows as they require.
- It has over 130 extractor components, which helps automate data collection for tools covered and not covered by Keboola’s ecosystem.
- It secures data at an enterprise-grade level by applying advanced security techniques regardless of your budget or availability of experts.
- Its flexible flow of data solutions allows various units to collaborate to help business expansions.
Etleap provides solutions for developing data pipelines with the help of monumental engineering resources. It automates most ETL setup and maintenance work and simplifies the rest in menial tasks. It helps small businesses to grow by exceeding user expectations with the help of an integrated data management solution. This paves ay for businesses to trust Etleap to effectively build their data pipelines.
Businesses have recognized that ‘loss of data’ is a very critical aspect, with the help of Etleap, they can avoid such blunders and focus on utilizing the information gathered.
Recently Etleap integrated with Amazon Redshift’s data sharing to provide isolation of ETL and BI workloads. Amazon Redshift is a fully managed cloud data warehouse that is a simple and cost-effective tool to analyze data using standard SQL. Etleap’s ETL solution automated most maintenance work and reduced set-up cost for Amazon Web Services.
Here, Amazon Redshift data sharing enables its customers to share data across different Amazon Redshift Clusters. It helps achieve workload isolation with secure and easy data sharing using configured SQL commands.
It leverages Etleap’s features like data sharing, throughout the life cycles of the ingestion pipeline. This process avoids maintaining data sharing between two clusters.
Key Features for businesses:
- Creation of perfect data pipelines from day one.
- It helps make complex data pipelines easier and faster for users to comprehend.
- Etleap helps users gain advanced intelligence from their data using its modeling feature.
- Etleap along with Amazon Redshift Materialized Views refreshed model tables faster and use fewer resources in the process. This frees up more resources for other workloads and allows engineer and analyst teams to work efficiently toward the desired goal.
- Etleap not only saves time spent on manual ETL and reports but allows a business to focus on high-value tasks for their growth and their client’s successes.
- It monitors collected data for businesses and controls the data flow.
Stitch is a cloud-first, developer-focused platform for rapidly moving data in a business. With businesses looking for solutions to increase sales and customer databases, Stitch’s solutions rapidly move data to analysts and other teams in a matter of minutes to work on them. Stitch connects to data sources like MySQL and MongoDB. It links tools like Zendesk and Salesforce to help replicate relevant data to data warehouses.
HousingAnywhere a rental accommodation platform for young professionals and international students began looking for SaaS ETL platforms at a lower price. The rental platform has over 8 million users across 60 countries. It offers direct API integrations and a dedicated payment system to manage rent transfers.
Here, they needed an easy and flexible tool to aggregate all their data sources in the Snowflake data warehouse. That is where Stitch’s “ease of use and smart pricing” entered the picture.
According to Massimo Belloni, Data Scientist at HousingAnywhere, “Stitch was really quick to set up, and since the price is based on row volume, that allowed us to replicate all our data sources.”
Key Features for businesses:
- Stitch enables businesses to quickly create and configure integrations as it allows programmatic control of one’s Stitch Account.
- It’s “ease of use and smart pricing” have helped multiple businesses with a lower budget and expansion goals to carry out their functions easily.
- It enables businesses to extract data from multiple sources and load it into their data warehouse.
- It offers a real-time evaluation of a user’s experience and businesses can utilize this insight to their benefit.
- It helps secure data by establishing a connection to a database by a private network without any firewall infiltrations.
- Based on your requirements businesses can configure Stitch to route different data sources from different destinations.
Free and Open-Source Software also known as FOSS, as the name suggests is both free and open-sourced. Anyone is allowed to use, copy, study and/or change the software in any way under a free license and the source code can be openly shared with the public, where they are encouraged to develop the design of the software as they please.
Businesses usually opt for FOSS as it is transparent and the codebase is open, there are no costs for using the tools as well.
Some of the notable FOSS solutions are petl, pandas, Apache Airflow, Postgres, Metabase, etc.
Key Features for businesses:
- FOSS is both free and open-sourced, which means no vendor costs or contractual obligations.
- It allows complete control over the software as well as flexibility in customization to the functions or codes. It also gives leeway to developers to distribute or not distribute the versions of the software and its rights.
- FOSS is often free of charge or comes at a very low cost, this encourages users to develop their software through tests and comparisons.
The segment is a leading Customer Data Platform that collects user events from a business’s website and mobile apps to provide complete data solutions to every team in that business. It personalizes customer interactions by unifying a business’s digital customer touchpoints across channels to understand the customer’s journey.
Businesses use Segment’s software and APIs to collect and control the customer’s data. In short, Segment enriches customer data by connecting the data from tools and then aggregates and monitors the performance that creates customized user experiences.
Bonobos, an eCommerce-driven apparel company, added a real-world component to the shopper’s journey. Here Bonobos wanted its customers to footfall to the physical stores and add on to their customers’ experience.
They ran Facebook ads to attract their target audiences, which helped their online market but affected their physical stores. That is where Segment provided a solution, where it helped Bonobos analyze the data that separated their online customers from the ones that visited the physical stores.
Segment integrated with the Facebook point-of-sale which enabled Bonobos to optimize its Facebook ads to attract audiences to their Guideshop locations and shop from those physical stores. As a result, with the help of Segment’s Facebook Offline Conversion integration, Bonobos increased their offline sales by 3X.
Key Features for businesses:
- Its data management solutions help businesses make sense of customer data collected from varied sources.
- Segment Persona helps increase efficiency in advertisements by analyzing the data as well as break it down for the sales and support team.
- It accelerates the A/B test practices which help refine any updates and allow users to share their feedback on the same.
- It helps analyze and optimize a business’s funnel to increase conversions by creating a “Retention Analysis” this is done by retracing the user’s steps on the platform.
- It generates messages about real-time updates on websites and apps, then formats it and notifies different tools called “Destinations”.
- Its servers also archive and replay historical data as well as send the data to the storage systems that can be exported when required.
- It also helps provide solutions on how a business can save time while complying with the GDPR and CCPA using Segment’s deletion features. The feature automates and complies with the regulations while respecting the user’s privacy.
Fivetran automated data integration is built on a fully managed ELT architecture that delivers zero-maintenance pipelines and ready-to-query schemas. It was built to allow analysts to access any data, at any given time.
It allows businesses to replicate applications much faster and is the smartest way to maintain a high-performance cloud warehouse. Data mappings allow businesses to connect their data sources with the destinations. It provides solutions that support vast lists of data sources that are incoming.
In 2019, Fivetran helped DocuSign regain engineering time and save money with the help of automated data pipelines. With the help of Fivetran connectors, DocuSign analyzed 3 times the sources than it could in the past. DocuSign saved the hassle of increasing their team size where Fivetran is able to achieve twice the results.
Key Features for businesses:
- The solutions are robust in nature and with the help of standardized schemas, automated pipelines enable businesses to focus on analysis and not ETL.
- Its agile nature allows businesses to study and analyze the data faster which also includes the newly added data sources.
- The solutions also include defined schemas and well-documented ERDs (Emergency Response Data Sheet), with no training or custom coding as well as access to all data in SQL.
- Its SOC 2 and GDPR compliance guarantees next-level data security by putting data encryption in motion.
- It has made data replication possible for businesses with less to no IT skillset by walking them through the entire process and the benefits that would help them advance.
Apache Spark is a unified analytics engine for large-scale data processing. It performs processing tasks on large sets of data and then distributes it across multiple sources. It distributes the data using its own solutions or by collaborating with other distributed computing tools.
It is a lightning-fast, open-source, distributed processing system that was created to address the limitations due to the sequential multi-step process. Earlier Hadoop MapReduce was the solution but it was slower with the response of the sequential multi-step data processing.
With Spark this latency is resolved by reusing data through the creation of Data-Frames, abstracting over Resilient Distributed Dataset (RDD), which makes it multiple times faster, specifically in machine learning.
Key Features for businesses:
- It is a lightning-fast solution that collects big data sets in its drivers and then processes them by distributing the sets to individual executors the work on the task assigned to them.
- It supports multiple languages through built-in APIs in Java, Scala, or Python.
- It was built to support Hadoop MapReduce but now it also supports SQL queries, machine learning, and streaming data.
Xplently is an ETL platform that enables businesses to integrate, process, and prepare data for analytics. Its scalable platform ensures businesses could benefit without investing in hardware or software by grabbing opportunities offered by big data.
It ensures businesses can have immediate access to different data sources as well as a large data set to analyze. It has allowed businesses to build pipelines as well as automate and transform the data, by loading it into the database and help analyze it.
Work4Labs helps Fortune 500 companies connect their social media, advanced analytics, and data. They needed an ETL solution to handle large datasets without errors and without experienced developers’ involvement. Their previous ETL solution involved complex coding which also utilized heavy amounts of time in continuous maintenance and manual work.
That is when Xplenty offered their easy-to-use, low code ETL solution where in just a few clicks data is migrated through sources without any coding. Work4 eliminated the use of developers to decode their data and enabled analysts to fix any data discrepancies.
Key Features for businesses:
- It simplifies ETL and ELT processes using low-code, multiple transformations, and a simple user-interface.
- Xplenty uses REST API connector which makes it agile for users to connect and extract data.
- It offers over 120 integrations to and from different sources which include databases, data warehouses, SaaS platforms BI tools such as Google BigQuery, Snowflake, Amazon Redshift, etc.
- It has a dedicated customer service team who are highly responsive via telephone, chat messaging and online meetings.
- It enables users without any prior coding experience to access, organize, view, and clean data.
- It also offers a 14 day trial on its platform for businesses to learn more about its solutions.
Conclusion:
Which tool do you think is best suited for your business?
Some big companies do build their own data pipelines like Netflix but it is an expensive venture. But for emerging businesses or non-technical businesses these tools provide help to build data pipelines at low costs.
These tools are compatible with popular data stores and SaaS platforms and generate revenue insights for a business. The tools have saved businesses time and money by analyzing real-time data streams.
Choose a solution that would complement your business at any stage it may be. With the above blog, you may have figured the best data pipeline tool to support your business and its requirements.
You May Also Like to Read:
Know more about Value Stream Mapping and the Steps required
Top 7 Open Source Master Data Management Tools
List of 6 Best Open Source Data Replication Tools
Understanding the Importance of Data Governance Maturity Model