Best Real-Time Data Streaming Tools for Small Business

StarTree Cloud is a fully-managed real-time analytics platform designed for OLAP at massive speed and scale for user-facing applications. Powered by Apache Pinot, StarTree Cloud provides enterprise-grade reliability and advanced capabilities such as tiered storage, scalable upserts, plus additional indexes and connectors. It integrates seamlessly with transactional databases and event streaming platforms, ingesting data at millions of events per second and indexing it for lightning-fast query responses. StarTree Cloud is available on your favorite public cloud or for private SaaS deployment. StarTree Cloud includes StarTree Data Manager, which allows you to ingest data from both real-time sources such as Amazon Kinesis, Apache Kafka, Apache Pulsar, or Redpanda, as well as batch data sources such as data warehouses like Snowflake, Delta Lake or Google BigQuery, or object stores like Amazon S3, Apache Flink, Apache Hadoop, or Apache Spark. StarTree ThirdEye is an add-on anomaly detection system running on top of StarTree Cloud that observes your business-critical metrics, alerting you and allowing you to perform root-cause analysis — all in real-time.

Apache Kafka®, is an open-source distributed streaming platform.

IBM Streams analyzes a wide range of streaming data, including unstructured text, video and audio, and geospatial and sensor data. This helps organizations to spot opportunities and risks, and make decisions in real-time.

Build and share real-time business dashboards without the hassle. Geckoboard integrates with over 80 tools and services to help you pull in your data and get a professional-looking dashboard in front of others in a matter of minutes. Create dashboards directly in your browser with a straightforward, drag-and-drop interface, and bring important numbers, metrics and KPIs out of lifeless reports. When ready, share your dashboard with a link, invite your teammates, schedule email and Slack updates to go out automatically. For maximum visibility, Geckoboard has ‘Send to TV’, allowing you to pair your account with a browser on a large screen or TV, and pick which dashboards you’d like displayed on there. It can even loop through several dashboard on one screen. We’ve got easy-to-follow instructions for how to achieve this in an afternoon using affordable off the shelf hardware.

Aiven manages your open-source data infrastructure in the cloud so that you don't have. Developers can do what is best for them: create applications. We do what we love: manage cloud data infrastructure. All solutions are open-source. You can also freely transfer data between clouds and create multi-cloud environments. You will know exactly what you will be paying and why. We combine storage, networking, and basic support costs. We will keep your Aiven software up and running. We will be there to help you if there is ever an issue. In 10 minutes, you can deploy a service on Aiven. 1. Register now - No credit card information required 2. Select your open-source service and choose the region and cloud to deploy to it 3. Select your plan and get $300 in credit 4. Click "Create service" to configure your data sources

Real-time analytics on raw data. Live ingest from S3, DynamoDB, DynamoDB and more. Raw data can be accessed as SQL tables. In minutes, you can create amazing data-driven apps and live dashboards. Rockset is a serverless analytics and search engine that powers real-time applications and live dashboards. You can directly work with raw data such as JSON, XML and CSV. Rockset can import data from real-time streams and data lakes, data warehouses, and databases. You can import real-time data without the need to build pipelines. Rockset syncs all new data as it arrives in your data sources, without the need to create a fixed schema. You can use familiar SQL, including filters, joins, and aggregations. Rockset automatically indexes every field in your data, making it lightning fast. Fast queries are used to power your apps, microservices and live dashboards. Scale without worrying too much about servers, shards or pagers.

Nussknacker allows domain experts to use a visual tool that is low-code to help them create and execute real-time decisioning algorithm instead of writing code. It is used to perform real-time actions on data: real-time marketing and fraud detection, Internet of Things customer 360, Machine Learning inferring, and Internet of Things customer 360. A visual design tool for decision algorithm is an essential part of Nussknacker. It allows non-technical users, such as analysts or business people, to define decision logic in a clear, concise, and easy-to-follow manner. With a click, scenarios can be deployed for execution once they have been created. They can be modified and redeployed whenever there is a need. Nussknacker supports streaming and request-response processing modes. It uses Kafka as its primary interface in streaming mode. It supports both stateful processing and stateless processing.

Aerospike is the global leader for next-generation, real time NoSQL data solutions at any scale. Aerospike helps enterprises overcome seemingly impossible data bottlenecks and compete with other companies at a fraction of the cost and complexity of legacy NoSQL databases. Aerospike's Hybrid Memory Architecture™ is a patented technology that unlocks the full potential of modern hardware and delivers previously unimaginable value. It does this by delivering unimaginable value from huge amounts of data at both the edge, core, and in the cloud. Aerospike empowers customers with the ability to instantly combat fraud, dramatically increase shopping cart sizes, deploy global digital payment networks, and provide instant, one-to-1 personalization for millions. Aerospike customers include Airtel and Banca d'Italia as well as Snap, Verizon Media, Wayfair, PayPal, Snap, Verizon Media, and Nielsen. The company's headquarters is in Mountain View, California. Additional locations are in London, Bengaluru, India, and Tel Aviv in Israel.

In the field of IoT stream processing and analytics, SQLstream ranks #1 according to ABI Research. Used by Verizon, Walmart, Cisco, and Amazon, our technology powers applications on premises, in the cloud, and at the edge. SQLstream enables time-critical alerts, live dashboards, and real-time action with sub-millisecond latency. Smart cities can reroute ambulances and fire trucks or optimize traffic light timing based on real-time conditions. Security systems can detect hackers and fraudsters, shutting them down right away. AI / ML models, trained with streaming sensor data, can predict equipment failures. Thanks to SQLstream's lightning performance -- up to 13 million rows / second / CPU core -- companies have drastically reduced their footprint and cost. Our efficient, in-memory processing allows operations at the edge that would otherwise be impossible. Acquire, prepare, analyze, and act on data in any format from any source. Create pipelines in minutes not months with StreamLab, our interactive, low-code, GUI dev environment. Edit scripts instantly and view instantaneous results without compiling. Deploy with native Kubernetes support. Easy installation includes Docker, AWS, Azure, Linux, VMWare, and more

Memgraph offers a light and powerful graph platform comprising the Memgraph Graph Database, MAGE Library, and Memgraph Lab Visualization. Memgraph is a dynamic, lightweight graph database optimized for analyzing data, relationships, and dependencies quickly and efficiently. It comes with a rich suite of pre-built deep path traversal algorithms and a library of traditional, dynamic, and ML algorithms tailored for advanced graph analysis, making Memgraph an excellent choice in critical decision-making scenarios such as risk assessment (fraud detection, cybersecurity threat analysis, and criminal risk assessment), 360-degree data and network exploration (Identity and Access Management (IAM), Master Data Management (MDM), Bill of Materials (BOM)), and logistics and network optimization. Memgraph's vibrant open-source community brings together over 150,000 developers in more than 100 countries to exchange ideas and optimize the next generation of in-memory data-driven applications across GenAI/ LLMs and real-time analytics performed with streaming data.

Materialize is a reactive database that provides incremental view updates. Our standard SQL allows developers to easily work with streaming data. Materialize connects to many external data sources without any pre-processing. Connect directly to streaming sources such as Kafka, Postgres databases and CDC or historical data sources such as files or S3. Materialize allows you to query, join, and transform data sources in standard SQL - and presents the results as incrementally-updated Materialized views. Queries are kept current and updated as new data streams are added. With incrementally-updated views, developers can easily build data visualizations or real-time applications. It is as easy as writing a few lines SQL to build with streaming data.

No more low-level code or gluing together complex systems. SQL makes it easy to build and deploy pipelines quickly. Data engineering service that allows developers and data engineers to quickly build and deploy data pipelines for data-driven apps. It is easy to connect to and find available data using pre-built connectors for messaging, storage, and database engines. Each connection you make will result in a stream of data to or from the system. You can create your pipelines using SQL with Decodable. Pipelines use streams to send and receive data to and from your connections. Streams can be used to connect pipelines to perform the most difficult processing tasks. To ensure data flows smoothly, monitor your pipelines. Create curated streams that can be used by other teams. To prevent data loss due to system failures, you should establish retention policies for streams. You can monitor real-time performance and health metrics to see if everything is working.

Pipes is a new way of creating queries and shaping data. It's inspired by Python Notebooks. This is a simplified way to increase performance without sacrificing complexity. Splitting your query into multiple nodes makes it easier to develop and maintain. You can activate your production-ready API endpoints in one click. Transforms happen on-the-fly, so you always have the most current data. You can share secure access to your data with one click, and get consistent results. Tinybird scales linearly, so don't worry if you have high traffic. Imagine if you could transform any Data Stream or CSV file into a secure real-time analytics API endpoint in a matter minutes. We believe in high-frequency decision making for all industries, including retail, manufacturing and telecommunications.

DeltaStream is an integrated serverless streaming processing platform that integrates seamlessly with streaming storage services. Imagine it as a compute layer on top your streaming storage. It offers streaming databases and streaming analytics along with other features to provide an integrated platform for managing, processing, securing and sharing streaming data. DeltaStream has a SQL-based interface that allows you to easily create stream processing apps such as streaming pipelines. It uses Apache Flink, a pluggable stream processing engine. DeltaStream is much more than a query-processing layer on top Kafka or Kinesis. It brings relational databases concepts to the world of data streaming, including namespacing, role-based access control, and enables you to securely access and process your streaming data, regardless of where it is stored.

Apache Doris is an advanced data warehouse for real time analytics. It delivers lightning fast analytics on real-time, large-scale data. Ingestion of micro-batch data and streaming data within a second. Storage engine with upserts, appends and pre-aggregations in real-time. Optimize for high-concurrency, high-throughput queries using columnar storage engine, cost-based query optimizer, and vectorized execution engine. Federated querying for data lakes like Hive, Iceberg, and Hudi and databases like MySQL and PostgreSQL. Compound data types, such as Arrays, Maps and JSON. Variant data types to support auto datatype inference for JSON data. NGram bloomfilter for text search. Distributed design for linear scaling. Workload isolation, tiered storage and efficient resource management. Supports shared-nothing as well as the separation of storage from compute.

Simplifies data transfer between components in microservices architectures. When used as a microservice transport, it simplifies integration and increases reliability. It also improves scaling. Read and write data near real-time. Set the data throughput to your needs. You can configure the resources to process data streams in granular detail, from 100 KB/s up to 100 MB/s. Yandex Data Transfer allows you to send a single data stream to multiple destinations with different retention policies. Data is automatically replicated over multiple geographically dispersed availability zones. Once created, data streams can be managed centrally via the management console or API. Yandex Data Streams is able to collect data continuously from sources such as website browsing histories, system and application logs, or social media feeds. Yandex Data Streams can continuously collect data from sources like website browsing histories, logs of application, etc.

Timeplus is an easy-to-use, powerful and cost-effective platform for stream processing. All in one binary, easily deployable anywhere. We help data teams in organizations of any size and industry process streaming data and historical data quickly, intuitively and efficiently. Lightweight, one binary, no dependencies. Streaming analytics and historical functionality from end-to-end. 1/10 of the cost of comparable open source frameworks Transform real-time data from the market and transactions into real-time insight. Monitor financial data using append-only streams or key-value streams. Implement real-time feature pipelines using Timeplus. All infrastructure logs, metrics and traces are consolidated on one platform. In Timeplus we support a variety of data sources through our web console UI. You can also push data using REST API or create external streams, without copying data to Timeplus.

SelectDB is an advanced data warehouse built on Apache Doris. It supports rapid query analysis of large-scale, real-time data. Clickhouse to Apache Doris to separate the lake warehouse, and upgrade the lake storage. Fast-hand OLAP system carries out nearly 1 billion queries every day in order to provide data services for various scenes. The original lake warehouse separation was abandoned due to problems with storage redundancy and resource seizure. Also, it was difficult to query and adjust. It was decided to use Apache Doris lakewarehouse, along with Doris's materialized views rewriting capability and automated services to achieve high-performance query and flexible governance. Write real-time data within seconds and synchronize data from databases and streams. Data storage engine with real-time update and addition, as well as real-time polymerization.

WarpStream, an Apache Kafka compatible data streaming platform, is built directly on object storage. It has no inter-AZ network costs, no disks that need to be managed, and it's infinitely scalable within your VPC. WarpStream is deployed in your VPC as a stateless, auto-scaling binary agent. No local disks are required to be managed. Agents stream data directly into and out of object storage without buffering on local drives and no data tiering. Instantly create new "virtual" clusters in our control plan. Support multiple environments, teams or projects without having to manage any dedicated infrastructure. WarpStream is Apache Kafka protocol compatible, so you can continue to use your favorite tools and applications. No need to rewrite or use a proprietary SDK. Simply change the URL of your favorite Kafka library in order to start streaming. Never again will you have to choose between budget and reliability.

HarperDB is an integrated distributed systems platform which combines database, caching and application functions into one technology. It allows you to deliver global back-end services at a lower cost, with higher performance and less effort. Install user-programmed apps and pre-built additions on top of data for a back end with ultra-low latencies. Distributed database with a high throughput per second, delivering orders of magnitude higher than NoSQL alternatives. Native real-time pub/sub data processing and communication via MQTT interfaces, WebSockets, and HTTP interfaces. HarperDB provides powerful data-in motion capabilities without adding additional services such as Kafka. Focus on features that will help your business grow, rather than fighting complicated infrastructure. You can't slow down the speed of light but you can reduce the amount of light between your users' data and them.

Amazon Managed Service For Apache Flink is used by thousands of customers to run stream-processing applications. Amazon Managed Service Apache Flink allows you to transform and analyze streaming data using Apache Flink in real-time and integrate applications with AWS services. There are no clusters or servers to manage and no computing infrastructure to install. You only pay for the resources that you use. You can build and run Apache Flink apps without having to manage resources or clusters, or set up infrastructure. Process gigabytes per second, with latencies of subseconds and respond to events instantly. Multi-AZ deployments, APIs for lifecycle management and APIs to manage application lifecycles help you deploy highly available and durable apps. Create applications that transform data and deliver it to Amazon Simple Storage Service (Amazon S3) and Amazon OpenSearch Service.

Easy to capture, transform and load streaming data. Create a stream of data, select the destination and start streaming real time data in just a few simple clicks. Automate the provisioning and scaling of compute, memory and network resources, without any ongoing administration. Transform streaming data into formats such as Apache Parquet and dynamically partition streaming without building your own pipelines. Amazon Data Firehose is the fastest way to acquire data streams, transform them, and then deliver them to data lakes, warehouses, or analytics services. Amazon Data Firehose requires you to create a stream that includes a destination, a source and the transformations required. Amazon Data Firehose continuously processes a stream, scales automatically based on data availability, and delivers the results within seconds. Select the source of your data stream, or write data with the Firehose Direct PUT (API) API.

The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.

Data integration for hybrid clouds Modern, reliable data integration across both your private cloud and public cloud. All this in real-time, with change data capture and streams. Striim was developed by the executive and technical team at GoldenGate Software. They have decades of experience in mission critical enterprise workloads. Striim can be deployed in your environment as a distributed platform or in the cloud. Your team can easily adjust the scaleability of Striim. Striim is fully secured with HIPAA compliance and GDPR compliance. Built from the ground up to support modern enterprise workloads, whether they are hosted in the cloud or on-premise. Drag and drop to create data flows among your sources and targets. Real-time SQL queries allow you to process, enrich, and analyze streaming data.

Apache Kafka®, with Confluent, has an infinite retention. Be infrastructure-enabled, not infrastructure-restricted Legacy technologies require you to choose between being real-time or highly-scalable. Event streaming allows you to innovate and win by being both highly-scalable and real-time. Ever wonder how your rideshare app analyses massive amounts of data from multiple sources in order to calculate real-time ETA. Wondering how your credit card company analyzes credit card transactions from all over the world and sends fraud notifications in real time? Event streaming is the answer. Microservices are the future. A persistent bridge to the cloud can enable your hybrid strategy. Break down silos to demonstrate compliance. Gain real-time, persistent event transport. There are many other options.