The world that we live in is driven by data. Gaining powerful real-time insights into real-world data lets your business have an edge. Data streaming allows the continuous capturing and processing of data originating from various data sources, and that’s why good streaming data platforms matter.
Data streaming platforms are scalable, distributed, and highly efficient systems that ensure the reliable processing of data streams. They support data aggregation and analysis and often come with a unified dashboard to visualize your data.
You can choose from a wide range of data streaming platforms and solutions — from fully managed systems like Confluent Cloud and Amazon Kinesis to open-source solutions like Arroyo and Fluvio.
What are some use cases for data streaming?
Data streaming platforms have a wide range of use cases that they cover. Let’s quickly go through a few of them:
- Fraud detection is handled by continuously analyzing transactions, user behavior, and patterns.
- Stock market trading data is captured by multiple systems that do blazing-fast high-volume trades based on market analysis.
- Custom insights through real-time market data provide e-commerce marketplaces with the right audience to target their products.
- There are millions of sensors in various systems providing real-world data and helping in predictive information like weather forecasts.
Here are the best data platforms for all your real-time analysis and stream processing needs.
Confluent Cloud
A fully cloud-native offering of Apache Kafka, Confluent Cloud provides resilience, scalability, and high performance. You get the power of the custom-built Kora engine that provides 10x better performance than running your own Kafka cluster. It brings you the following features:
- Serverless clusters offer you scalability and elasticity. You can instantly meet your data streaming requirements with on-demand automatic scale-up and shrink-down.
- Your data storage requirements are met with infinite data retention and data integrity. With no durability issues, you can make Confluent Cloud your source of truth.
- Confluent Cloud offers an uptime SLA of 99.99%, one of the industry’s best. Paired with multi-zone replication, you get protected against data corruption or loss.
The Stream Designer empowers you with a drag-and-drop UI to visually create your processing pipeline. In addition, the pre-built Kafka connectors let you plug into any app or data provider.
Confluent Cloud provides you with Stream Governance, the industry’s only data governance suite which is fully managed. Having enterprise-grade cloud security and compliance allows you to safeguard your data and control access.
Confluent Cloud offers different pricing options. It also offers a wide range of resources to help you dive right in.
Aiven
Aiven helps you run your data streaming needs in a fully managed Apache Kafka cloud service. It supports all the major cloud providers, including AWS, Google Cloud, Microsoft Azure, Digital Ocean, and UpCloud.
Set up your own Kafka service in less than 10 minutes using either the web console or programmatically via the API and CLI. Additionally, you get the option of running it in containers.
Skip the hassle of worrying about Kafka management with a fully managed cloud service. You can have your data pipeline quickly set up along with a monitoring dashboard. Let’s take a look at the benefits you’ll be getting:
- Receive automatic updates for your cluster and manage your version upgrades and maintenance with just a few clicks.
- Aiven provides you with 99.99% uptime and near-zero interruptions.
- Increase your storage on demand, add more Kafka nodes, or deploy to different regions.
Aiven’s monthly pricing starts from $200 and varies based on your location and the cloud provider you opt for.
Arroyo
If you’re looking for a truly cloud-native and open-source solution for your real-time analysis and processing, Arroyo is a great tool. It’s powered by the Arroyo Streaming Engine — a distributed stream processing solution that shines when it comes to real-time data lookup with sub-second results.
Arroyo is built to make real-time processing as easy as batch processing. Being highly user-friendly by design, you don’t need to be an expert to build your pipeline. Here’s what you get with Arroyo:
- There’s native support for different connectors, including Kafka, Pulsar, Redpanda, WebSockets, and Server Sent Events.
- After data ingestion and processing, the outgoing results can be written into various systems — like Kafka, Amazon S3, and Postgres.
- You get a state-of-the-art, efficient, and high-performing compiler that transforms your SQL queries to run with maximum efficiency.
- The data flow for your data platforms can scale horizontally to support millions of events per second.
You can run your self-hosted instance of Arroyo, which is free, or take the help of Arroyo Cloud, starting at $200 per month. However, Arroyo is currently in Alpha and may have missing features.
Amazon Kinesis
Amazon Kinesis Data Streams enables you to collect and process large data streams for rapid and continuous ingestion. It has massive scalability, durability, and low cost. Let’s look at the top features you get:
- Amazon Kinesis runs on the AWS cloud in an on-demand serverless mode. With a few clicks from the AWS Management Console, you can have your Kinesis Data streams running.
- You can have Kinesis running in up to 3 Availability Zones (AZs). It also offers 365 days of data retention.
- Kinesis Data streams allow you to attach up to 20 consumers. Also, each consumer has its own dedicated read throughput and can publish within 70 milliseconds of ingestion.
- Meet your security requirements by encrypting your data using server-side encryption.
- Being a part of AWS lets Kinesis seamlessly integrate with other AWS services like Cloudwatch, DynamoDB, and AWS Lambda.
With Amazon Kinesis, you pay for what you use. Considering 1000 records/second of 3 KB each, your daily cost for an on-demand mode for starters will be roughly $30.61. You can use the AWS calculator to find out your usage-based cost.
Databricks
If you’re looking for a single data platform for both batch and stream processing, the Databricks Lakehouse Platform is a great choice. Additionally, you get real-time analytics, machine learning, and applications on one platform.
The Databricks Lakehouse Platform has its own data view called Delta Live Tables (DLT) with the following benefits:
- DLT lets you easily define your end-to-end data pipeline.
- You get automatic data quality testing. Simultaneously you can monitor data quality trends over time.
- If your workload is unpredictable, then DLT’s enhanced autoscaling handles it.
You get the best place to run your Apache Spark workloads, with Spark Structured Streaming as the core technology. Coupled with this is Delta Lake, the only open-source storage platform which supports both streaming and batch data.
With the Databricks Lakehouse Platform, you can enjoy a 14-day free trial, after which you’ll be automatically subscribed to the plan that you’ve been on.
Qlik Data Streaming (CDC)
CDC or Change Data Capture is the technique by which any change in data is notified to other systems. A simple and universal solution, Qlik Data Streaming (CDC) allows you to easily move your data from source to destination in real-time. You get to manage everything through a simple graphical interface.
Qlik Data Streaming (CDC) provides a streamlined and automatic configuration. Thus, you can easily set up, control, and monitor your real-time data pipeline.
You get the support of a broad range of sources, targets, and platforms. This allows you to not only ingest a wide variety of data but also synchronize on-premise, cloud, and hybrid data.
The Qlik Enterprise Manager is your central command center which lets you scale easily and monitor data flow through alerts.
There is a flexible deployment option when it comes to choosing how you want to run your CDC pipeline. Based on your requirement, you can choose between the following:
- If you’re looking for a platform as a service, then go for Qlik Cloud Data Integration
- If you’d rather manage it on your own, then you can install Qlik Data Integration on-premise.
You can get started with a free trial without downloading or installing anything.
Fluvio
Looking for an open-source cloud-native streaming solution with low latency and high performance? Fluvio fits that description. You gain the ability to perform inline computations using SmartModules that enhance the functionality of the Fluvio platform.
Fluvio has distributed stream processing with checks to prevent data loss and downtime. Additionally, there’s native API support for popular programming languages like Rust, Node.js, Python, Java, and Go. Let’s take a look at what the platform has in store for you:
- The power of combining computation with streaming in a unified cluster gives you minimized delays.
- Fluvio dynamically loads custom modules that extend computational capabilities.
- You get high scalability that ranges from small IoT devices to multi-core systems.
- It has auto-healing capabilities using declarative management, reconciliation, and replication.
- Because it was built with the developer community in mind, you get a powerful CLI for efficiency.
Be it your laptop, your enterprise data center, or your public cloud of choice, you can install Fluvio on any platform.
Due to the fact that it’s open-source, there are no charges for running Fluvio.
Cloudera Stream Processing (CSP)
Powered by Apache Flink and Apache Kafka, Cloudera Stream Processing (CSP) provides you with analyzing capabilities to gain insights into your streaming data. It has native support for standard technologies like SQL and REST. Additionally, you get a complete stream management solution combined with stateful processing that is built for enterprises.
Cloudera Stream Processing reads and analyzes high volumes of real-time data to produce results within subsecond latencies. Get support for multi-cloud and hybrid cloud, along with the necessary tools to build highly sophisticated data-driven analytics. Enjoy the following tools and features:
- Supporting millions of messages per second, you can keep up with your ever-changing needs with highly scalable streaming.
- Streams Messaging Manager offers an end-to-end view of how your data moves across your data processing pipeline.
- Streams Replication Manager offers replication, availability, and disaster recovery.
- Mitigate schema mismatches and interruptions with Schema Registry which lets you manage everything in a shared repository.
- An automatically enforced centralized security, Cloudera SDX offers unified control and governance across all your components.
With Cloudera Stream Processing in less than 10 minutes, you can spin up your stream processing pipeline on the cloud platform of your choice — be it AWS, Azure, or Google Cloud Platform.
Striim Cloud
Do your data platform and real-time analysis need a wide variety of data producers and consumers? Striim Cloud, with inbuilt support for 100+ connectors, can be the perfect choice. Easily integrate with your existing data stores and stream real-time data with the help of a fully managed SaaS platform designed for the cloud.
Striim Cloud offers a simple drag-and-drop interface, that not only helps build your pipeline but also provides insights into your data. It supports the most popular analytics tools, including Google BigQuery, Snowflake, Azure Synapse, and Databricks. In addition to it, you get the following:
- Your worries about changes in the data structure are handled by Striim’s schema evolution capabilities. You can configure it for automatic resolution or manual intervention.
- Built on distributed streaming SQL platform, Striim lets you run continuous queries.
- Striim offers high scalability and throughput. Subsequently, you can scale your pipeline without any additional planning or cost.
- The ‘ReadOnlyWriteMany’ method enables you to add and remove new targets without any impact on your data stores.
Pay only for what you use. The Striim developer environment is free and lets you try out the platform with 10 million events/month. For an enterprise-scale cloud solution, it starts at $2500/month.
VK Streaming Data Platform
With the highest standard of data products and insights, Vertical Knowledge (VK) helps individuals and businesses make powerful decisions at scale. VK Streaming Data Platform allows you to process massive amounts of data through a web-based data streaming environment.
Get actionable insights with automated data discovery. Here are the key benefits of VK’s Streaming Data Platform:
- You get robust cyber security due to VK’s stable infrastructure that protects you from malicious content. Also, you can download data through a virtual environment.
- Automated data streams allow you to operate across multiple data sources with ease.
- With rapid discovery, you can reduce manual processes, which are often time-consuming.
- Generate deep data collections by running concurrent pipelines from multiple sources. Thus, you can generate global results for selected keywords.
- You can export your data collections in raw JSON or CSV format or use APIs to integrate with third-party systems.
HStream Platform
Built on the open-source HStreamDB, the HStream Platform offers a serverless streaming data platform. You can ingest massive amounts of data and reliably store millions of data streams. HStreamDB is as fast as Kafka. Additionally, you can replay historical data
You can use SQL to filter, transform, aggregate, and even join multiple data views. Thus, you gain real-time insights into your data. HStream Platform lets you start off small and is lean. Here are the key features:
- Being serverless, it’s ready to use right from the start.
- There’s no need for Kafka for your streaming needs.
- You get in-place stream processing using standard SQL.
- Consume from and produce to different systems, be it databases, data warehouses, or data lakes. So, there’s no need for additional ETL tools.
- You can efficiently manage all your workload in one unified streaming platform.
- The cloud-native architecture lets you scale your computing and storage needs independently.
HStream Platform is currently in public beta. It’s free to use — all you need to do is sign up for it.
Conclusion
Choosing a good data streaming platform depends on your scale, need for different connectors, uptime, and reliability.
While some platforms are fully managed services, others are open-source and provide you with various customizations. Take a look at your needs and budget and choose the one that works best for you.
Next up, are you still wondering how you can make the best use of all that data? Try AI-powered data forecasting and prediction tools for businesses.
