Grafana is particularly recommended for IT professionals, data analysts, and engineers who need to monitor and visualize large datasets in real-time. It's ideal for organizations running complex systems or applications that require comprehensive monitoring to ensure uptime and performance are maintained. Additionally, Grafana is suitable for teams that value open-source solutions and require a platform that can integrate with multiple data sources and adapt to various monitoring needs.
Based on our record, Grafana seems to be a lot more popular than Spark Streaming. While we know about 240 links to Grafana, we've tracked only 5 mentions of Spark Streaming. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.
Monitoring and Logging: Tools like Prometheus and Grafana provide instant observability. - Source: dev.to / 8 days ago
Grafana is a leading open-source platform for monitoring, visualization, and observability. Since its initial launch in 2014, Grafana has grown to become the standard for time series analytics, with over 68,000 GitHub stars and a thriving ecosystem of plugins and integrations. The platform allows users to query, visualize, alert on, and understand metrics no matter where they're stored, enabling the creation of... - Source: dev.to / 9 days ago
Navigate to Grafana Cloud and sign up or log in. In the sidebar, select Connections → Add new connection, select Loki. This is the place that prompts you to set up your Loki connection and allows you to generate an access token for Alloy. - Source: dev.to / 30 days ago
Prometheus + Grafana: Open-source tools that offer maximum flexibility without ongoing licensing costs—ideal for teams willing to manage their own infrastructure and configuration. - Source: dev.to / about 1 month ago
Prometheus: This open-source monitoring solution pairs with Grafana for powerful custom visualization of exactly what matters to your business. - Source: dev.to / about 1 month ago
The last decade saw the rise of open-source frameworks like Apache Flink, Spark Streaming, and Apache Samza. These offered more flexibility but still demanded significant engineering muscle to run effectively at scale. Companies using them often needed specialized stream processing engineers just to manage internal state, tune performance, and handle the day-to-day operational challenges. The barrier to entry... - Source: dev.to / about 1 month ago
Apache Spark Streaming: Offers micro-batch processing, suitable for high-throughput scenarios that can tolerate slightly higher latency. https://spark.apache.org/streaming/. - Source: dev.to / 9 months ago
Other stream processing engines (such as Flink and Spark Streaming) provide SQL interfaces too, but the key difference is a streaming database has its storage. Stream processing engines require a dedicated database to store input and output data. On the other hand, streaming databases utilize cloud-native storage to maintain materialized views and states, allowing data replication and independent storage scaling. - Source: dev.to / over 1 year ago
Spark Streaming: The component for real-time data processing and analytics. - Source: dev.to / over 2 years ago
Is a big data framework and currently one of the most popular tools for big data analytics. It contains libraries for data analysis, machine learning, graph analysis and streaming live data. In general Spark is faster than Hadoop, as it does not write intermediate results to disk. It is not a data storage system. We can use Spark on top of HDFS or read data from other sources like Amazon S3. It is the designed... - Source: dev.to / over 3 years ago
Prometheus - An open-source systems monitoring and alerting toolkit.
Confluent - Confluent offers a real-time data platform built around Apache Kafka.
Datadog - See metrics from all of your apps, tools & services in one place with Datadog's cloud monitoring as a service solution. Try it for free.
Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.
Zabbix - Track, record, alert and visualize performance and availability of IT resources
Google Cloud Dataflow - Google Cloud Dataflow is a fully-managed cloud service and programming model for batch and streaming big data processing.