Companies acquire massive amounts of data online in today’s digital age. You’ll have to transform the raw data to create usable data, whether gathering data from various sources or creating dashboards and visualizations. This is when ETL comes into play.
ETL pipelines help to carry out these processes easily. Hence, the usage of ETL tools has increased as data is quickly expanding, thus resulting in a spike in demand for the finest ETL tools in Data Warehouse.
Here’s all you need to know about ETL tools, as well as the best 19 ETL Tools in 2024.
What is ETL?
ETL stands for Extract, Transform, and Load. It is defined as a Data Integration service and allows companies to combine data from various sources into a single, consistent data store that is loaded into a Data Warehouse or any other target system.
What are ETL Tools?
ETL tools are applications/platforms that enable users to execute ETL processes. In simple terms, these tools help businesses move data from one or many disparate data sources to a destination. These help in making the data both digestible and accessible (and in turn analysis-ready) in the desired location – often a data warehouse.
How ETL Tool Works?
There are 3 steps that are involved in the ETL process namely:
- Extraction: In this, the structured or unstructured data is extracted from its source and consolidated into a single repository. ETL tools automate the extraction process and create a more efficient and reliable workflow for handling large volumes of data and multiple sources.
- Transformation: In order to improve data integrity the data needs to be transformed such as it needs to be sorted, standardized, and redundant data should be removed. This step ensures that raw data which arrives at its new destination is fully compatible and ready to use.
- Loading: This is the final step of the ETL process which involves loading the data into the final destination(data lake or data warehouse). The data can be loaded all at once(full load) or at scheduled intervals(incremental load).
Best 19 ETL Tools for 2024
1) Hevo Data
Hevo Data allows you to replicate data in near real-time from 150+ Data Sources to the destination of your choice including Snowflake, BigQuery, Redshift, and Databricks without writing a single line of code. Finding patterns and opportunities is easier when you don’t have to worry about maintaining the pipelines. So, with Hevo as your data pipeline platform, maintenance is one less thing to worry about.
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For rare times things go wrong, Hevo Data ensures zero data loss. To find the root cause of an issue, Hevo Data also lets you monitor your workflow so that you can address the issue before it derails the entire workflow. Add 24*7 customer support to the list, and you get a reliable tool that puts you at the wheel with greater visibility. Check Hevo’s in-depth documentation to learn more.
If you don’t want SaaS tools with unclear pricing that burn a hole in your pocket, opt for a tool that offers a simple, transparent Hevo Pricing model. Hevo Data has 3 usage-based pricing plans starting with a free tier, where you can ingest up to 1 million records.
Hevo was the most mature Extract and Load solution available, along with Fivetran and Stitch but it had better customer service and attractive pricing. Switching to a Modern Data Stack with Hevo as our go-to pipeline solution has allowed us to boost team collaboration and improve data reliability, and with that, the trust of our stakeholders on the data we serve.
– Juan Ramos, Analytics Engineer, Ebury
Check out how Hevo empowered Ebury to build reliable data products here.
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Pentaho is a key Business Intelligence software that provides OLAP services, Data Integration, reporting, Data Mining, information dashboards, Data Mining, and ETL platform capabilities. By utilizing Pentaho you can transform complex data into meaningful reports and extract valuable information from it.
Pentaho allows you to create reports in numerous formats like Excel, PDF, Text, CSV, HTML, and XML.
Here are the key features of Pentaho:
- Pentaho relies heavily on multi-cloud-based and hybrid architectures.
- Pentaho provides Data Processing and Data Integration features from multiple data sources.
- It is built to focus on on-premise, batch ETL use cases.
- Pentaho works based on the interpretation of ETL procedures stored in XML format. Pentaho is better than a lot of its competitors since there is no code generation involved.
- It can be deployed on a cloud provider or in an on-premise provider.
ETL Tools: 3) Talend
Talend allows you to handle every stage of the Data Lifecycle and puts healthy data at your fingertips. Talend offers Data Integration, Data Integrity, Governance, API, and Application Integration.
Talend also offers support for virtually every cloud Data Warehouse and all major public cloud infrastructure providers.
Here are the key features of Talend:
- Talend Studio offers a User Interface to design the flow and transformation logic.
- It supports most on-premise and cloud databases with connectors to various software-as-a-service offerings.
- Talend functions based on a code generation approach. This means that the code has to be built every time there is a change in logic.
- Talend works best with Batch processes.
- Talend’s ace up its sleeve is in the area of hybrid cloud and multi-cloud. This is an area where customers with extremely high Data Protection requirements manage with more than on-premise and cloud systems.
4) AWS Glue
AWS Glue is known as a serverless ETL software service that sifts through your data, performs Data Preparation, Data Ingestion, Data Transformation, and builds a Data Catalog. AWS Glue offers all the capabilities required for Data Integration so that you can start analyzing your data.
You can then put it to use within minutes as opposed to months. AWS Glue offers code-based and visual interfaces to make Data Integration simpler. Users can easily access and find data using the AWS Glue Data Catalog.
Here are the key features of AWS Glue:
- AWS Glue is mainly batch-oriented, but it can also support near real-time use cases based on Lambda functions.
- AWS Glue, in tandem with Lambda functions, allows it to implement a serverless full-fledged ETL vendor.
- It offers a pay-as-you-go pricing model that charges an hourly rate, billed by the second.
- AWS Glue offers numerous noteworthy features – automatic schema discovery and an integrated Data Catalog.
5) Informatica PowerCenter
Informatica PowerCenter offers a high-performance, scalable enterprise Data Integration solution that supports the entire Data Integration lifecycle. PowerCenter can easily deliver data on-demand which includes batch, real-time or Change Data Capture (CDC). It is also capable of managing the broadest range of Data Integration initiatives as a single platform.
Here are the key features of Informatica PowerCenter:
- Informatica PowerCenter simplifies the development of Data Marts and Data Warehouses.
- It meets the requirements for security, scalability, and collaboration through the capabilities like Data Masking, Metadata Management, Dynamic Partitioning, and High Availability.
- It is mainly one of the best batch-based ETL tools.
- It offers integrations to popular Cloud Data Warehouses like DynamoDB, Amazon Redshift, etc.
6) Azure Data Factory
Azure Data Factory is known as a serverless, fully-managed Data Integration service. With Azure Data Factory, you can easily construct an ETL platform without any prerequisite coding knowledge. You can then deliver integrated data to Azure Synapse Analytics to unearth valuable insights to guide business growth.
Here are the key features of Azure Data Factory:
- Azure Data Factory is cost-effective since it allows you to enjoy a pay-as-you-go pricing model.
- Azure Data Factory allows you to ingest all your Software as a Service (SaaS) and software data with over 90 built-in connectors.
- You can use Azure Data Factory to rehost SQL Server Integration Services in a few clicks with built-in CI/CD and Git support.
- You can use autonomous ETL to unlock operational efficiencies while enabling citizen integrators.
7) IBM Infosphere DataStage
IBM Infosphere DataStage is an ETL tool that is a part of the IBM Infosphere and IBM Information Platforms Solutions suite. It leverages a graphical notation to construct Data Integration solutions. You can avail of multiple versions of IBM Infosphere DataStage like the Enterprise Edition, Server Edition, and the MVS Edition.
Here are the key features of IBM Infosphere DataStage:
- IBM Infosphere DataStage is a batch-based ETL tool.
- It is an enterprise product focused on bigger organizations with legacy data systems.
- You can cut Data Movement costs with containers and virtualizations.
- With IBM Infosphere DataStage, you can easily separate ETL job design from runtime and deploy it on any cloud.
- It allows you to run any workload 30% faster with a parallel engine and workload balancing.
- You can also extend capabilities while preserving the key DataStage investments.
Blendo allows you to access your cloud data from Marketing, Sales, Support, or accounting to accelerate data-driven Business Intelligence and grow faster. Blendo supports natively built Data Connection types that make the ETL process a breeze. It allows you to automate Data Transformation and Data Management to get to BI insights faster.
Here are the key features of Blendo:
- With trustworthy data, analytics-ready schemas, and tables, you can accelerate your exploration to insights time, created and optimized for analysis with any BI software.
- You can sync and automate from any SaaS application into your Data Warehouse.
- You can use ready-made connectors to connect to any data source, which helps save countless hours and help you unearth actionable insights for your business.
- You can create integrations with inputs like HubSpot, MailChimp, Mixpanel, Salesforce, Shopify, Stripe, MySQL, Google Ads, and Facebook Ads among many more in a matter of minutes.
The StreamSets DataOps platform allows you to power your digital transformation and modern analytics with continuous data. It allows you to monitor, build, and run smart Data Pipelines at scale from a single point of login.
StreamSets can quickly build and deploy batch, streaming, ML, CDC, and ETL pipelines. It also allows you to manage and monitor all your Data Pipelines from a single pane of glass.
Here are the key features of StreamSets:
- With flexible Hybrid and Multi-Cloud deployment, you can move easily between on-premises and multiple cloud environments without rework.
- You can reduce maintenance time by 80% with automatic updates and no rewrites.
- You can control gaps and eliminate blindspots through global transparency and control of all Data Pipelines at scale across Multi-Cloud and Hybrid frameworks.
- StreamSets allow you to keep jobs running even when structures and schemas change.
Integrate.io is widely known as a Data Integration, ETL platform that streamlines Data Processing and saves valuable time. This allows your business to focus on insight instead of getting stuck with Data Preparation. It provides users with jargon and a coding-free environment that has a point-and-click interface. This enables simple Data Integration and Data Processing.
Here are the key features of Integrate.io:
- Integrate.io allows you to connect to over 140 sources including Data Warehouses, Databases, and Cloud-based SaaS platforms.
- You can leverage Integrate.io’s Data Security team with the Integrate.io platform’s Security Transformation features to ensure that your data is stored in a compliant and secure manner.
- Integrate.io provides unlimited support by video and phone for all users to ensure a smooth User Experience.
- Integrate.io is an easy-to-setup platform, that can handle millions of records per minute without latency.
Xtract.io is well-known as a web data extraction service that allows you to accelerate your data-driven global business using AI-powered Data Aggregation and Extraction. You can grow your business with their suite of enterprise-grade platforms and solutions.
Xtract.io believes in building tailored solutions which provide their customers the flexibility and agility that they seek. Xtract.io also gives precise location data for you to get accurate and detailed insights into your market, customers, competitors, and product.
Here are the key features of Xtract.io:
- Xtract.io utilizes AI/ML technologies like Image Recognition, NLP, and Predictive Analytics to deliver accurate information.
- It also combines data from a plethora of sources, removes duplicates, and enriches them. This allows the data to be more consumable.
- Xtract.io builds powerful APIs to push a steady stream of fresh data directly into your premises. This includes both on-premises and in-cloud frameworks.
- Xtract.io’s powerful dashboards and reports let decision-makers and analysts make quick data-driven decisions at a glance.
Jaspersoft is widely regarded as a leader in the Data Integration segment that focuses on ETL. It is a part of the Jaspersoft Business Intelligence Suite that offers a customizable, flexible, and developer-friendly Business Intelligence platform tailored to each customer’s needs.
Here are the key features of Jasper:
- It allows you to build data visualizations and reports to exact design specifications.
- With Multi-tenant support, you can manage security to data and access resources for all your SaaS customers.
- It allows you to deploy using any method. It is 100% open architecture and can be run anywhere on anything. You can design, manage, and embed analytics and reports with programmatic control easily.
13) Sybase ETL
Sybase ETL includes the Sybase ETL Server and Sybase ETL Development. Sybase ETL Development is a GUI (Graphical User Interface) that is used for designing and creating Data Transformation projects and jobs. It provides a complete simulation and debugging environment that is designed to speed up the development of ETL Transformation flows.
Sybase ETL Server is a distributed and scalable grid engine that connects to data sources and extracts and loads data to data targets using Transformation Flows.
Here are the key features of Sybase ETL:
- It provides the ability to extract data from numerous sources like Sybase IQ, Sybase ASE, Oracle, Microsoft Access, Microsoft SQL Server, and many more.
- It allows you to load data into a target database through delete, updating and inserting statements, or in bulk.
- It provides you with the ability to cleanse, merge, convert, and split data streams. This can then be used to insert, update, or delete data in a data target.
14) SAP BusinessObjects Data Integrator
This is a Data Integration and ETL platform that allows you to extract data from any source, and transform, integrate, and format that data into any target database. The focus of this tool is to extract and transform data.
This tool also provides a basic set of commands to cleanse and document your data. Apart from this, the transformations or applied business rules are built via a graphical user interface. This makes it easy to follow through with your workflows.
Here are the key features of SAP BusinessObjects Data Integrator:
- SAP BusinessObjects Data Integrator allows you to execute, schedule, and monitor batch jobs.
- You can use this tool to build any type of Data Mart or Data Warehouse as well.
- It provides support for Sun Solaris, Windows, AIX, and Linux platforms.
Skyvia is a Cloud Platform that offers cloud-to-cloud backup, data access via OData Interface, management via SQL, and no-coding Data Integration. Skyvia is highly scalable since it has flexible pricing plans for every product which makes it suitable for all types of companies ranging from enterprise companies to small startups.
It also offers contemporary Cloud agility that eliminates the need for manual upgrades or deployment.
Here are the key features of Skyvia:
- Skyvia provides you with the ability to preserve source data relations in the target.
- It also offers data import without duplicates complete with bi-directional synchronization.
- Skyvia also gives you pre-defined templates for common Data Integration scenarios.
- You can easily automate data collection from disparate Cloud sources to a Data Warehouse or database.
- You can easily migrate your business data between cloud apps automatically with just a few clicks.
16) Oracle Data Integrator
Oracle Data Integrator is an ETL solution that enables users to create, deploy, and manage sophisticated data warehouses. It has pre-configured connectors for a variety of databases, including EREPs, Hadoop, CRMs, XML, JDBC, JSON, ODBC, and LDAP.
ODI features Data Integrator Studio, which allows business users and developers to access numerous artifacts via a graphical user interface. These artifacts provide all aspects of data integration, including data transfer, synchronization, quality, and management.
17) Google Cloud Dataflow
Google Cloud offers Dataflow, a serverless ETL solution. It supports both batch and stream data processing and doesn’t require organizations to possess a server or cluster. Instead, customers simply pay for the resources they use, which scale dynamically based on needs and workloads.
Google Dataflow runs Apache Beam pipelines inside the GCP ecosystem. Apache provides Python, Go, and Java SDKs for representing and transporting data collections, both batch and streaming. This allows users to select the most suitable SDK for defining their data flow.
Hadoop is an open-source framework for storing and processing large amounts of data across multiple computer servers. It is regarded as the foundation of big data, allowing for large-scale data storage and processing.
The Hadoop framework is made up of various modules, like the Hadoop Distributed File System (HDFS) for data storage, MapReduce for data processing, and YARN for resource management. Hive is often used for converting SQL queries into MapReduce jobs.
Organizations considering Hadoop should be mindful of the associated costs. Rather than the tools or storage, a substantial percentage of the expense of installing Hadoop is due to the computing power necessary for processing and the expertise required to maintain Hadoop ETL.
19) SAS Data Management
SAS Data Management integrates with a variety of sources and transfers data to a recognized destination without the need for ETL processes. SAS Data Management provides the ETL features required to integrate data from a relational database, CRM platform, transactional database, or other source.
One of SAS Data Management’s strongest characteristics is its ability to move data quickly from a source to a warehouse for data analysis. ETL data to a warehouse allows you to build meaningful reports and other data visualizations in BI tools to help you make better decisions.
Use of ETL Tools?
Once the loading step is completed in the ETL process, the ETL tool sets the stage for long-term analysis and usage of such data. The ETL tools break down data silos and make it accessible for the data scientist to analyze data, and turn it into business intelligence.
More dependency on data warehousing makes cloud-based ETL tools more important for organizations.
In short, ETL tools are the first essential step in the data warehousing process that eventually lets you make more informed decisions in less time.
What are the types of ETL Tools?
The expansiveness of ETL tools has developed quickly as associations have embraced new data warehousing and data lake technologies and deployed more streaming and CDC ETL software integration patterns. Now organizations can choose from various types of ETL tools according to their need.
The 4 types of ETL tools are:
Enterprise ETL Tools
The ETL tools are often bundled as part of a larger platform and appeal to enterprises with older, legacy systems that they need to work with and build on. These ETL tools can handle pipelines efficiently and are highly scalable since they were one of the first to offer ETL tools and mature in the market. These tools support most relational and non-relational databases.
Custom ETL Tools
In this, the custom tools and pipelines are created using scripting languages like SQL or Python. While this gives you an opportunity for customization and higher flexibility, it also requires more administration and maintenance.
Cloud-Based ETL Tools
These tools integrate with proprietary data sources and ingest data from different web apps or on-premises sources. These tools move data between systems and copy, transform, and enrich data before writing it to data warehouses or data lakes.
Open-Source ETL Tools
With the rise of open-source tools, it’s no surprise that open-source ETL tools have also emerged. Many ETL tools today are free and provide easy-to-use user interfaces for designing data exchange processes and monitoring the flow of information. An advantage of open-source solutions is that organizations can access the source code to study the tool infrastructure and extend the functionality.
Modern applications need real-time data for processing purposes. So, what is an ETL tool, and which are the best available tools?
Numerous ETL Tools available in the market can simplify the Data Management task while improving Data Warehousing. These tools can help you save valuable time, effort, and money.
In this article, you will be taking a look at a few open-source free tools and some commercial, licensed tools that can cater to your business requirements.
How to select an ETL Tool?
The following factors must be considered while selecting an ETL tool:
Maintenance is a critical factor as it defines a lot about the pipeline’s success. Answering the below questions might help in understanding the maintenance factors of an ETL tool:
- What would be the technical requirements of your team to maintain the pipelines?
- How easy will it be to map the data if there are frequent changes in the data sources?
- How quickly can the issues be debugged and fixed?
Although most of the tools would be simple to use at any point, some technical issues or glitches could arise. It’s important to look at how simple to understand the documentation of the ETL, and how responsive is the email and call support.
Cost is one of the most important factors while carrying out any task. Answering the below questions might help in selecting a tool:
- What would be the initial costs of building your pipelines?
- What would be the yearly costs of maintaining the pipelines?
- How simple to understand the pricing model?
Most ETL tools provide integrations for commonly used data sources. If any tool supports all the integrations you need, it will save you significant time. Although it’s possible that no single tool would support all the data sources, but if the tool you select can connect to the S3 bucket, then there shouldn’t be much of a hassle as the S3 bucket would act as an intermediate between the source and the ETL tool.
If your team can effectively manage and take advantage of any open-source ETL tools, then for organizations with significant in-house development capabilities, there are additional options that can be very cost-effective and can fulfill your ETL needs.
This blog discusses the 19 best ETL tools currently present in the market. Based on your requirements, you can leverage one of these to boost your productivity through a marked improvement in operational efficiency.
Businesses can choose either paid or free open-source data replication tools. While paid tools usually have quality support, up-to-date documentation, and regular product updates to keep up with the changes in the databases and customer requirements. Free Open-Source tools allow businesses to customize the tool as per their requirements.
Extracting complex data from a diverse set of data sources can be a challenging task, and this is where Hevo saves the day! Hevo is the only real-time ELT No-code Data Pipeline platform that cost-effectively automates data pipelines that are flexible to your needs from integration with 150+ Data Sources (40+ free sources).
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