Modern-day businesses use multiple SaaS applications and Databases to store the data. Extracting and integrating all of this data can assist you in visualizing your complete business performance. Traditionally, the engineering teams are assigned with writing custom scripts for building and maintaining data ingestion pipelines. As a business grows, developing, monitoring & fixing pipelines becomes a time-consuming job as the data volumes & sources also rise.
Opting for Real time Data Ingestion Tools allows you to set up data pipelines in just a few clicks. All of these are monitored and maintained by the service providers with minimal downtime for maintenance. Apart from extracting and loading data, these real time Data Ingestion Tools offer features such as data cleansing, data profiling, data enrichment, etc.
In this article, you will learn about the best Real time Data Ingestion Tools.
Table of Contents
- What is Data Ingestion?
- How does Data Ingestion work?
- What are Data Ingestion Tools?
- How to Choose the right Data Ingestion Tool?
- Key Real time Data Ingestion Tools
- What are the Challenges of Manual Data Ingestion?
What is Data Ingestion?
Data Ingestion is the process of streaming large amounts of data from multiple different external sources to your target system to perform the ad-hoc queries, analytics, and other operations that your business requires. Simply defined, Data Ingestion requires you to consume data from the source system, clean & prepare it, and finally load it to your desired destination.
How does Data Ingestion work?
Massive volumes of data is generated regularly from apps, IoT devices, social networks, user events, etc. This data is stored & maintained in separate systems from which you have to extract it and load it into a destination or a staging area. Generally, a simple data ingestion pipeline might only apply a few lightweight transformations such as cleaning, filtering, enriching, etc. before loading it into a data store, data warehouse, or a message queue. You can also perform complex transformation joins, aggregates, and sorts for specific analytics, that can be added via external pipelines. This process can be designed to be continuous, Real time, batched, or asynchronous according to your data needs.
Best Real Time Data Ingestion Tools
In this article, you will learn about various Real time Data Ingestion Tools you could use to achieve your data goals. Hevo Data fits the list as an ETL and Real Time Data Ingestion Tool that helps you load data from 100+ data sources (including 40+ free sources) into a data warehouse or a destination of your choice. Adding to its flexibility, Hevo provides several Data Ingestion Modes such as Change Tracking, Table, Binary Logging, Custom SQL, Oplog, etc.Get Started with Hevo for Free
Here’s a list of Best Real Time Data Ingestion Tools:
What are Data Ingestion Tools?
With the growing demand for Real-time data for business intelligence, building and maintaining data ingestion pipelines manually has become a time-consuming & resource-intensive task. Real-time Data Ingestion Tools assist you in simplifying this process by automatically extracting data from multiple sources and transferring it to the desired destination. Real-time Data Ingestion tools also help in processing, modifying & formatting data to correctly match the target system schema.
Data Ingestion: Build vs Buy
Building a custom Data Ingestion solution according to your business needs will have an upper hand over opting for a third-party tool that only solves parts of the problem. In some cases, you may even feel that building a solution in-house gives you complete control and visibility of your data.
However, to design, develop, & manage this solution, you need to assign a portion of engineering bandwidth that has to continuously monitor the pipeline. You also need to ensure that your solution is scalable. For that, you have to invest heavily in buying and maintaining infrastructure as well. Lastly, you are also required to have comprehensive documentation and proper knowledge transfer to eliminate any dependencies.
Real-time Data Ingestion tools, on the other hand, establish a framework for businesses that allows them to collect, transfer, integrate, & process data from multiple sources. Without worrying about building & managing the ever-evolving data connector, Real-time Data Ingestion Tools provides a seamless data extraction process with complete support for several data transport protocols. Along with data collection, integration & processing, Real-time data ingestion tools also has data modification & formatting capabilities to facilitate analytics. You can either start the data ingestion process in batches(small chunks of data) or stream it in Real-time.
Hence, depending on your business use case, available engineering bandwidth, and other resources, you can decide to make the optimal choice between buying or building a Data Ingestion Tool!
Key Benefits of Data Ingestion Tools
Employing Real-time Data Ingestion Tools allows you to leverage the following benefits:
- Better Performance: With little to no time & effort spent on setting up and maintaining pipelines, Real-time Data Ingestion tools completely manages the whole process efficiently.
- Scalability: As a business grows, bo the number of data sources & the data volume increases at an exponential rate. Real-time Data Ingestion Tools ensure that they easily scale on-demand and can effectively handle fluctuating workloads.
- Data Transformation: You can also perform data formatting, data cleaning & data profiling operations using the Real-time data ingestion tools. Acting as a one-stop solution for data transformation processes, Real-time data ingestion tools help you save a lot of time in data analytics by proving analysis-ready data.
- Easy to Use: Most Real-time Data Ingestion Tools provide a user-friendly interface that allows any beginner to quickly get started with their first data ingestion pipeline. This also eliminates the need for expert technical knowledge, allowing data analysts to initiate a data ingestion pipeline by selecting the data source and the destination.
- Improved Data Management: With minimal manual intervention during the data transfer process, Real-time Data Ingestion tools maintain data quality and reduce any inaccuracies or redundancies.
How to Choose the right Data Ingestion Tool?
There are several Real-time Data Ingestion Tools, though you need to select the optimal tool that suits your business needs. To ease out the selection process, you can check out the following checklist:
- One of the main concerns of any firm is how protected is their data. Ensure that the Real-time data ingestion tool has data security mechanisms and policies in place.
- Whether it is a developer or someone from the business team, the Real-time Data Ingestion tools should be easily operable without requiring any technical knowledge.
- While selecting your tool, define your requirements clearly like is it scalable, can it process external data semantics, how quickly the pipeline issues are resolved, how resilient it is to network errors, etc.
- An open-source Real-time data ingestion tool is always a good idea as now you have the flexibility to customize it according to your needs.
- Efficient Real-time Data Ingestion tools perform the data transfer process much faster. Ensure that it also has an effective data cleansing system.
- It is always an advantage to have insights into data in Real-time. If possible, try out the free trials of the Real-time data ingestion tools to have a feel of the architectural design of the product and observe its ability to integrate with your existing system.
Key Real-time Data Ingestion Tools
Some of the popular Real-time Data Ingestion tools are as follows:
- Hevo Data
- Apache Kafka
- Apache Nifi
- Amazon Kinesis
- Elastic Logstash
Hevo provides an Automated No-code Data Pipeline that assists you in ingesting data in real-time from 100+ data sources but also enriching the data and transforming it into an analysis-ready form without having to write a single line of code. Its fault-tolerant architecture ensures that the data is handled in a secure, consistent manner with zero data loss. Adding to its flexibility, Hevo provides several Data Ingestion Modes such as Change Tracking, Table, Binary Logging, Custom SQL, Oplog, etc.
Hevo’s fault-tolerant architecture will enrich and transform your data securely and consistently and load it to your destination without any assistance from your side. You can entrust us with your data transfer process by both ETL and ELT processes to a data warehouse, Reverse ETL processes to CRMs, etc and enjoy a hassle-free experience.
Here are more reasons to try Hevo:
- Smooth Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to your schema in the desired Data Warehouse.
- Exceptional Data Transformations: Best-in-class & Native Support for Complex Data Transformation at fingertips. Code & No-code Flexibility is designed for everyone.
- Quick Setup: Hevo with its automated features, can be set up in minimal time. Moreover, with its simple and interactive UI, it is extremely easy for new customers to work on and perform operations.
- Built To Scale: As the number of sources and the volume of your data grows, Hevo scales horizontally, handling millions of records per minute with very little latency.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
Apache Kafka is one of the Popular Open-Source Distributed Stream Real time Data Ingestion Tools & Processing platforms. Providing an end-to-end solution to its users, Kafka can efficiently read & write streams of events in Real time with constant import/export of your data from other data systems.
Its Reliability & Durability allows you to store streams of data securely for as long as you want. With its Best-in-Class performance, Low latency, Fault Tolerance, and High Throughput, Kafka can handle & process thousands of messages per second in Real-time.
Launched as an Open Source Messaging Queue System by LinkedIn in 2011, Kafka has now evolved into a Full-Fledged Event Streaming Platform. Among other Real-time Data Ingestion Tools, it is an excellent choice for building Real-time Streaming Data Pipelines and Applications that adapt to the Data Streams. You can easily Install Kafka on Mac, Windows & Linux OS. Adding to its Flexibility, Kafka works for both Online & Offline Message Consumption.
Apache Nifi is one of the popular open-source Real time Data Ingestion Tools for distributing and processing data with support for data routing and transformation. It is an integration, automation tool to perform data ingestion at a faster pace. Compared to other Real time Data Ingestion Tools, Apache Nifi uses a robust system that processes and distributes the data over several resources. You can work with Apache NiFi in both standalone mode and cluster mode.
It allows you to get incoming messages, filters, and formats using several processors. Most of all, Apache Nifi is fault-tolerant, leverages automation, manages the flow of information between systems, and promotes data lineage, security, and scalability.
With Amazon Kinesis, you can easily collect, process, and analyze Real time streaming data to gain important insights and take the required actions based on the latest. Amazon Kinesis provides key capabilities with cost-effective processing of streaming data of all sizes, giving you the flexibility to select the right tool for your application needs. Compared to other Real time Data Ingestion Tools, with Amazon Kinesis you can capture Real time data such as video, audio, application logs, website clickstreams, machine learning, analytics, etc.
With Amazon Kinesis, you can process and analyze your data when it arrives, and respond immediately without having to wait for all your data to be captured before you start processing. Configuring the Kinesis Data Stream and Kinesis Data Firehose Stream, you can set up the data ingestion and loading process.
Wavefront is a SaaS-based, enterprise observability solution that allows you to visualize, alert and query data. Compared to other Real time Data Ingestion Tools, you can employ Wavefront to ingest time-series metrics, histograms, traces and spans logs. You can transfer data from multiple data sources to Wavefront through several integrations, a Wavefront proxy, or through direct ingestion. Based on a stream processing approach developed at Google, Wavefront allows you to manipulate metric data with unparalleled power.
Wavefront provides a simple yet powerful query language that allows you to query high-dimensional data. The query language is easy to understand, yet powerful enough to deal with high-dimensional data. Like other powerful Real time Data Ingestion Tools, Wavefront can ingest millions of data points per second.
Funnel is a cloud-hosted ETL platform specifically built for marketers. Its data connector allows users to collect data from over multiple data sources for cleaning, grouping, and mapping. Funnel also provides complete support for several data destinations, including reporting tools and data warehouses. In Funnel, you can also retrieve the raw basic data as it stores historical data. For data transformations, you can map, tag, or segment data using standard and custom rules.
Adverity is a powerful end-to-end data analysis platform built for marketing teams. Among other Real time Data Ingestion Tools, this platform provides automatic data ingestion from multiple data sources, allowing users to visualize their data streams from a centralized dashboard. This complete view of your marketing performance is powered by stunning data visualization and predictive analytics. With advanced schema mapping capabilities, you can easily deal with consistent data structures to meet your reporting and analysis needs. To protect your data, Adverity follows international data protection standards such as the EU General Data Protection Regulation (GDPR).
Using Talend Data Fabric service, you can retrieve data from multiple data sources and establish a connection with any target system such as a data warehouse, database, or cloud service. Users can also use the drag-and-drop mechanism to create reusable and scalable data ingestion pipelines. Compared to other Real time Data Ingestion Tools, this platform also provides data quality services for error detection and correction. Whether in the cloud or on-premises, Talend offers functionalities that allow enterprise users to manage larger datasets suitable for large organizations.
Elastic Logstash is an open-source data processing pipeline that allows you to extract data from multiple sources and transfer it to your desired target system. These data sources include logs, metrics, web applications, data stores, and various AWS services. No matter the data format or complexity, Logstash can transform or parse your data on the fly. Compared to other Real time Data Ingestion Tools, Elastic Logstash can derive structure from unstructured data with grok, decipher geo coordinates from IP addresses, anonymize or exclude sensitive fields, and ease overall processing.
Improvado is one of the popular Real time data ingestion built for marketing purposes. Automating all the mundane data operations, Improvado reduces the unnecessary tasks of marketing analysts and lets them concentrate on their core objectives. It streamlines the data ingestion process & provides pre-built data extraction patterns that allow marketers to start retrieving data right after integration is done. Compared to other Real time Data Ingestion Tools, Improvado allows you to ingest data in batches with an hourly data synchronization frequency.
What are the Challenges of Manual Data Ingestion?
While performing Data Ingestion manually from multiple data sources, you might face the following challenges:
- Slow Process: Every data source has different data formats and file structures. While extracting data from multiple sources stored in different data formats, different syntax, or attached metadata, you need to transform it into an analysis-ready form. Converting data to the right form takes a considerable amount of time and resources. From the data source to the data warehouse, the whole process is divided into several stages. At each stage, data needs to be verified and validated to meet the organization’s security standards. With conventional data cleansing methods and systems, this costumes a lot of unnecessary time.
- Complex: When setting up a data processing & analytics system, you have to ensure that all the individual tools & frameworks keep up with the ever-evolving data connectors. If these tools are not adaptable, you would need to write custom codes and maintain the features according to the external data sources.
- Errors: As you start running your data ingestion pipelines, you are eventually bound to have some errors and need to fix the issues as soon as possible. As data moves through different stages, you need to ensure data quality and data consistency. This will again require your engineering team to spend additional time on building, monitoring & maintaining data security, & data quality protocols.
In this article, you have learned about the top Real time Data Ingestion tools. In the Data Ingestion process, you need to extract data from data systems where the data is originally created or stored and transfer it to your desired destination. To simplify the data ingestion process, you can use the Real time Data Ingestion Tools that can automatically retrieve data from several sources, perform the desired transformation such as data cleansing & profiling and load it into your target system.
As you collect and manage your data across several applications and databases in your business, it is important to consolidate it for complete performance analysis of your business. However, it is a time-consuming and resource-intensive task to continuously monitor the Data Connectors. To achieve this efficiently, you need to assign a portion of your engineering bandwidth to Integrate data from all sources, Clean & Transform it, and finally, Load it to a Cloud Data Warehouse, BI Tool, or a destination of your choice for further Business Analytics. All of these challenges can be comfortably solved by a Cloud-based ETL tool such as Hevo Data.Visit our Website to Explore Hevo
Hevo Data, a No-code Data Pipeline can Ingest Data in Real-Time from a vast sea of 150+ sources to a Data Warehouse, BI Tool, or a Destination of your choice. It is a reliable, completely automated, and secure service that doesn’t require you to write any code!
If you are using CRMs, Sales, HR, and Marketing applications and searching for a no-fuss alternative to Manual Data Integration, then Hevo can effortlessly automate this for you. Hevo, with its strong integration with 150+ sources and BI tools(Including 40+ Free Sources), allows you to not only export & load data but also transform & enrich your data & make it analysis-ready in a jiffy.