In the modern era, companies highly rely on data to predict trends, forecast the market, plan for future needs, understand consumers, and make business decisions. However, to accomplish such tasks, it is critical to have quick access to enterprise data in one centralized location. The task of collecting and storing both structured and unstructured data in a centralized location is called Big Data Ingestion.
This article introduces Big Data Ingestion and discusses its importance. Moreover, there are various Big Data Ingestion tools available in the market with unique features and functionalities. In this article, you will learn about data ingestion and top big data ingestion tools in 2022. Read along to choose the right tool for your business!
Table of Contents
- What is Big Data Ingestion?
- Top Big Data Ingestion Tools in 2022
What is Big Data Ingestion?
Big data ingestion involves, assembling data from various sources in different formats and loading it to centralized storage such as a Data lake or a Data Warehouse. The stored data is further accessed and analyzed to facilitate data-driven decisions. Data processing systems can include data lakes, databases, and dedicated storage repositories. While implementing data ingestion, data can either be ingested in batches or streamed in real-time. When data is ingested in batches, it is imported in discrete chunks at regular intervals, whereas in real-time data ingestion, each data item is continuously imported as it is emitted by the source.
Top Big Data Ingestion Tools in 2022
Top Big Data Ingestion Tools in 2022
Choosing a Big Data Ingestion tool that can support your Data Team’s needs can be a challenging task, especially when the market is full of similar tools. To simplify your task, here is a list of the 8 best Big Data Ingestion Tools in the market:
Big Data Ingestion Tools: Hevo Data
Hevo Data, a No-code Data Pipeline helps to load data from any data source such as MySQL, SaaS applications, Cloud Storage, SDK,s, and Streaming Services and simplifies the ETL process. It supports 100+ data sources and loads the data onto the desired Data Warehouse, enriches the data, and transforms it into an analysis-ready form without writing a single line of code.
Its completely automated pipeline offers data to be delivered in real-time without any loss from source to destination. Its fault-tolerant and scalable architecture ensure that the data is handled in a secure, consistent manner with zero data loss and supports different forms of data. The solutions provided are consistent and work with different Business Intelligence (BI) tools as well.Get Started with Hevo for Free
Check out why Hevo is the Best:
- Secure: Hevo has a fault-tolerant architecture that ensures that the data is handled in a secure, consistent manner with zero data loss.
- Schema Management: Hevo takes away the tedious task of schema management & automatically detects the schema of incoming data and maps it to the destination schema.
- Minimal Learning: Hevo, with its simple and interactive UI, is extremely simple for new customers to work on and perform operations.
- Hevo Is 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.
- Incremental Data Load: Hevo allows the transfer of data that has been modified in real-time. This ensures efficient utilization of bandwidth on both ends.
- Live Support: The Hevo team is available round the clock to extend exceptional support to its customers through chat, email, and support calls.
- Live Monitoring: Hevo allows you to monitor the data flow and check where your data is at a particular point in time.
Big Data Ingestion Tools: Apache Nifi
Apache NiFi is specifically designed to automate large data flow between software systems. It takes advantage of the ETL concept to provide low latency, high throughput, guaranteed delivery, and loss tolerance. The Apache NiFi data ingestion engine uses schemaless processing technology, which means that each NiFi processor interprets the content of the data it receives.
Apache NIFI supports directed graphs of data routing, transformation, and system mediation logic that are powerful and scalable. The web-based user interface, seamless experience between design, control, feedback, monitoring, data provenance, SSL, SSH, HTTPS, and encrypted content generation are some of ApacheNiFi’s high-level capabilities. Unlike its peer tools, Apache Nifi leverages a robust data processing and distribution system to channel multiple resources. Apache Nifi can be used in both standalone and cluster modes. It enables you to receive incoming messages, filter them, and format them using multiple processors.
Since Apache Nifi is an open-source data ingestion platform, you can download and get unlimited access to every Nifi offering free of cost.
Big Data Ingestion Tools: Apache Flume
Apache Flume is a distributed and resilient service for efficiently collecting, aggregating, and moving large amounts of log data. It is fault-tolerant and robust, with tunable reliability mechanisms and numerous failover and recovery mechanisms. Apache Flume is primarily intended for data ingestion into a Hadoop Distributed File System (HDFS). The tool extracts, aggregates, and loads massive amounts of streaming data from various sources into HDFS.
While Apache Flume is primarily used to load log data into Hadoop, it supports other frameworks such as Hbase and Solr. Apache Flume stands out for its ease of use, robustness, fault tolerance, and tunable reliability mechanisms.
Apache Flume is free to download since it is an open-source platform.
Big Data Ingestion Tools: Apache Kafka
Apache Kafka is an open-source big data ingestion software that is Apache-licensed and used for high-performance data pipelines, streaming analytics, data integration, and other purposes. It can deliver data at network-limited throughput with latencies as low as 2ms using a group of machines.
Apache Kafka is written in Scala and Java, and it can use Kafka Connect to connect with external or third-party applications for data importing and exporting tasks. Since it is open-source, the platform has a large ecosystem of community-driven tools to assist users in gaining additional functionality.
Apache Kafka is completely free to download and use since it is an open-source platform. However, to use the Kafka connectors that come with the Confluent subscription, you must pay according to the basic, standard, or dedicated plans.
Big Data Ingestion Tools: Wavefront
Wavefront is a high-performance streaming analytics service hosted in the cloud for ingesting, storing, visualizing, and monitoring all types of metric data. The platform is capable of scaling rapidly for high query loads, reaching even millions of data points per second. It is based on a Google-invented stream processing approach that enables engineers to manipulate metric data with unprecedented power.
Wavefront is capable of ingesting millions of data points per second, and users can manipulate data in real-time and deliver actionable insights by leveraging an intuitive query language. It enables users to collect data from over 200 different sources and services, such as DevOps tools, cloud service providers, big data services, and others. Wavefront users can view data in custom dashboards, receive alerts on problem values, and perform functions like anomaly detection and forecasting.
The monthly pricing for Wavefront starts at $1.50/datapoint/second (PPS). The $15/host/month estimate assumes that each host generates 100 data points every 10 seconds on average over a month. This price is based on the Wavefront Telegraf agent, which provides detailed infrastructure metrics with a resolution of up to 1 second and additional capacity for custom and application. However, Wavefront also offers a free trial for a limited period.
Big Data Ingestion Tools: Amazon Kinesis
Amazon Kinesis is a powerful and automated cloud-based service that empowers businesses to extract, & analyze real-time data streams. The platform can capture, process, and store both videos (via Kinesis Video Streams) and data streams (using Kinesis Data Streams).
Using the Kinesis Data Firehose, Amazon Kinesis captures and processes terabytes of data per hour from hundreds of thousands of data sources. This implies that Amazon Kinesis can manage terabytes of data per hour from hundreds of thousands of sources, including website clickstreams, financial transactions, social media feeds, IT logs, and location-tracking events.
Amazon Kinesis provides key capabilities for the cost-effective processing of streaming data of all sizes, allowing you to choose the best tool for your application requirements. With Amazon Kinesis, you can collect, process, and analyze data as it arrives and responds immediately, rather than having to wait for all of your data to be captured before processing.
The pricing of the Amazon Kinesis varies depending on your AWS region. You can use the AWS Pricing Calculator to estimate the total price of Amazon Kinesis based on your requirements and use cases.
Big Data Ingestion Tools: Talend
Talend’s unified data service called Talend Data Fabric allows you to pull data from 1000 data sources. You can then connect them to the destination of your choice, such as a cloud service, data warehouse, or database. Google Cloud Platform, Amazon Web Services, Snowflake, Microsoft Azure, and Databricks are among the cloud services and data warehouses that the service supports. In addition, Talend Data Fabric’s drag-and-drop feature allows you to create scalable and reusable pipelines.
When compared to other Real-Time Data Ingestion Tools, Talend also offers data quality services for error detection and correction. Whether in the cloud or on-premises, Talend provides enterprise users with the ability to manage larger datasets suitable for large organizations.
The pricing of Talend is based on its subscription plans like Data Management Platform, Big Data Platform, and Data Fabric. On its pricing site, Talend does not disclose the pricing details. For more information on their services, users should contact the sales team or request a demo.
Big Data ingestion Tools: Apache Gobblin
Apache Gobblin is a universal data ingestion framework for extracting, transforming, and loading large data volumes from multiple sources into HDFS. Gobblin handles routine data ingestion ETL tasks such as task partitioning, error correction, data quality management, and so on. It is capable of ingesting big data from various external sources within the same execution framework and manages all of the metadata from these various sources in one location.
Gobblin-is-a-service feature capitalizes on the containerization trend by allowing Gobblin jobs to be containerized and run independently from other jobs. Similarly, Gobblin’s core engine is designed for ingestion in a microservice-based world, with optimizations such as pipelining remote service calls to hide latency and blocking capabilities in connectors to prevent DDOS of online services from ingestion traffic.
Since Apache Gobblin is an open-source data ingestion platform, you can download and get unlimited access to every Gobblin offering free of cost.
In this article, you learned about data ingestion and top big data ingestion tools in 2022. This article only focused on seven of the most popular data ingestion tools. However, there are other data ingestion tools available in the market with other unique features and functionalities. You can further explore the features and capabilities of other data ingestion tools and use them on your data pipelines based on the use cases and requirements.Visit our Website to Explore Hevo
Hevo Data is one of the most popular Big Data Ingestion Tools. It is a no-code, cloud-based platform built for ELT platforms (extract, transform, and load). It supports data loading from any source into the Data Warehouse of your choice in real-time. Hevo is a fully managed data pipeline solution that provides ten times faster reporting and analysis. The platform is great for companies as it requires zero maintenance, is easy to set up, and can support 100+ integrations across cloud storage, streaming services, databases, and more. Also, you do not require to write custom configuration as it is a fully automated platform.
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