Best Data Management Software for InfluxDB

Cribl Stream allows you create an observability pipeline that helps you parse and restructure data in flight before you pay to analyze it. You can get the right data in the format you need, at the right place and in the format you want. Translate and format data into any tooling scheme you need to route data to the right tool for the job or all of the job tools. Different departments can choose different analytics environments without the need to deploy new forwarders or agents. Log and metric data can go unused up to 50%. This includes duplicate data, null fields, and fields with zero analytical value. Cribl Stream allows you to trim waste data streams and only analyze what you need. Cribl Stream is the best way for multiple data formats to be integrated into trusted tools that you use for IT and Security. Cribl Stream universal receiver can be used to collect data from any machine source - and to schedule batch collection from REST APIs (Kinesis Firehose), Raw HTTP and Microsoft Office 365 APIs.

Redis Labs is the home of Redis. Redis Enterprise is the best Redis version. Redis Enterprise is more than a cache. Redis Enterprise can be free in the cloud with NoSQL and data caching using the fastest in-memory database. Redis can be scaled, enterprise-grade resilience, massive scaling, ease of administration, and operational simplicity. Redis in the Cloud is a favorite of DevOps. Developers have access to enhanced data structures and a variety modules. This allows them to innovate faster and has a faster time-to-market. CIOs love the security and expert support of Redis, which provides 99.999% uptime. Use relational databases for active-active, geodistribution, conflict distribution, reads/writes in multiple regions to the same data set. Redis Enterprise offers flexible deployment options. Redis Labs is the home of Redis. Redis JSON, Redis Java, Python Redis, Redis on Kubernetes & Redis gui best practices.

Elastic is a search company. Elasticsearch, Kibana Beats, Logstash, and Elasticsearch are the founders of the ElasticStack. These SaaS offerings allow data to be used in real-time and at scale for analytics, security, search, logging, security, and search. Elastic has over 100,000 members in 45 countries. Elastic's products have been downloaded more than 400 million times since their initial release. Today, thousands of organizations including Cisco, eBay and Dell, Goldman Sachs and Groupon, HP and Microsoft, as well as Netflix, Uber, Verizon and Yelp use Elastic Stack and Elastic Cloud to power mission critical systems that generate new revenue opportunities and huge cost savings. Elastic is headquartered in Amsterdam, The Netherlands and Mountain View, California. It has more than 1,000 employees in over 35 countries.

When seeking a database that ensures both scalability and high availability without sacrificing performance, Apache Cassandra stands out as an ideal option. Its linear scalability paired with proven fault tolerance on standard hardware or cloud services positions it as an excellent choice for handling mission-critical data effectively. Additionally, Cassandra's superior capability to replicate data across several datacenters not only enhances user experience by reducing latency but also offers reassurance in the event of regional failures. This combination of features makes it a robust solution for organizations that prioritize data resilience and efficiency.

Apache Kafka® is a robust, open-source platform designed for distributed streaming. It can scale production environments to accommodate up to a thousand brokers, handling trillions of messages daily and managing petabytes of data with hundreds of thousands of partitions. The system allows for elastic growth and reduction of both storage and processing capabilities. Furthermore, it enables efficient cluster expansion across availability zones or facilitates the interconnection of distinct clusters across various geographic locations. Users can process event streams through features such as joins, aggregations, filters, transformations, and more, all while utilizing event-time and exactly-once processing guarantees. Kafka's built-in Connect interface seamlessly integrates with a wide range of event sources and sinks, including Postgres, JMS, Elasticsearch, AWS S3, among others. Additionally, developers can read, write, and manipulate event streams using a diverse selection of programming languages, enhancing the platform's versatility and accessibility. This extensive support for various integrations and programming environments makes Kafka a powerful tool for modern data architectures.

Telegraf is an open-source server agent that helps you collect metrics from your sensors, stacks, and systems. Telegraf is a plugin-driven agent that collects and sends metrics and events from systems, databases, and IoT sensors. Telegraf is written in Go. It compiles to a single binary and has no external dependencies. It also requires very little memory. Telegraf can gather metrics from a wide variety of inputs and then write them into a wide range of outputs. It can be easily extended by being plugin-driven for both the collection and output data. It is written in Go and can be run on any system without external dependencies. It is easy to collect metrics from your endpoints with the 300+ plugins that have been created by data experts in the community.

Enhance your metrics and alerting capabilities using a top-tier open-source monitoring tool. Prometheus inherently organizes all data as time series, which consist of sequences of timestamped values associated with the same metric and a specific set of labeled dimensions. In addition to the stored time series, Prometheus has the capability to create temporary derived time series based on query outcomes. The tool features a powerful query language known as PromQL (Prometheus Query Language), allowing users to select and aggregate time series data in real time. The output from an expression can be displayed as a graph, viewed in tabular format through Prometheus’s expression browser, or accessed by external systems through the HTTP API. Configuration of Prometheus is achieved through a combination of command-line flags and a configuration file, where the flags are used to set immutable system parameters like storage locations and retention limits for both disk and memory. This dual method of configuration ensures a flexible and tailored monitoring setup that can adapt to various user needs. For those interested in exploring this robust tool, further details can be found at: https://sourceforge.net/projects/prometheus.mirror/

NGINX Open Source is the web server that supports over 400 million websites globally. Built upon this foundation, NGINX Plus serves as a comprehensive software load balancer, web server, and content caching solution. By opting for NGINX Plus instead of traditional hardware load balancers, organizations can unlock innovative possibilities without being limited by their infrastructure, achieving cost savings of over 80% while maintaining high performance and functionality. It can be deployed in a variety of environments, including public and private clouds, bare metal, virtual machines, and container setups. Additionally, the integrated NGINX Plus API simplifies the execution of routine tasks, enhancing operational efficiency. For today's NetOps and DevOps teams, there is a pressing need for a self-service, API-driven platform that seamlessly integrates with CI/CD workflows, facilitating faster app deployments regardless of whether the application utilizes a hybrid or microservices architecture, which ultimately streamlines the management of the application lifecycle. In a rapidly evolving technological landscape, NGINX Plus stands out as a vital tool for maximizing agility and optimizing resource utilization.

PostgreSQL stands out as a highly capable, open-source object-relational database system that has been actively developed for more than three decades, earning a solid reputation for its reliability, extensive features, and impressive performance. Comprehensive resources for installation and usage are readily available in the official documentation, which serves as an invaluable guide for both new and experienced users. Additionally, the open-source community fosters numerous forums and platforms where individuals can learn about PostgreSQL, understand its functionalities, and explore job opportunities related to it. Engaging with this community can enhance your knowledge and connection to the PostgreSQL ecosystem. Recently, the PostgreSQL Global Development Group announced updates for all supported versions, including 15.1, 14.6, 13.9, 12.13, 11.18, and 10.23, which address 25 reported bugs from the past few months. Notably, this marks the final release for PostgreSQL 10, meaning that it will no longer receive any security patches or bug fixes going forward. Therefore, if you are currently utilizing PostgreSQL 10 in your production environment, it is highly recommended that you plan to upgrade to a more recent version to ensure continued support and security. Upgrading will not only help maintain the integrity of your data but also allow you to take advantage of the latest features and improvements introduced in newer releases.

Effortlessly gather, manage, and scrutinize video and data streams as they occur. Amazon Kinesis simplifies the process of collecting, processing, and analyzing streaming data in real-time, empowering you to gain insights promptly and respond swiftly to emerging information. It provides essential features that allow for cost-effective processing of streaming data at any scale while offering the adaptability to select the tools that best align with your application's needs. With Amazon Kinesis, you can capture real-time data like video, audio, application logs, website clickstreams, and IoT telemetry, facilitating machine learning, analytics, and various other applications. This service allows you to handle and analyze incoming data instantaneously, eliminating the need to wait for all data to be collected before starting the processing. Moreover, Amazon Kinesis allows for the ingestion, buffering, and real-time processing of streaming data, enabling you to extract insights in a matter of seconds or minutes, significantly reducing the time it takes compared to traditional methods. Overall, this capability revolutionizes how businesses can respond to data-driven opportunities as they arise.

Aggregate all your data seamlessly using Enterprise plugins such as Splunk, ServiceNow, Datadog, and others. The integrated collaboration tools enable teams to engage efficiently from a unified dashboard. With enhanced security and compliance features, you can rest assured that your data remains protected at all times. Gain insights from experts in Prometheus, Graphite, and Grafana, along with dedicated support teams ready to assist. While other providers may promote a "one-size-fits-all" database solution, Grafana Labs adopts a different philosophy: we focus on empowering your observability rather than controlling it. Grafana Enterprise offers access to a range of enterprise plugins that seamlessly integrate your current data sources into Grafana. This innovative approach allows you to maximize the potential of your sophisticated and costly monitoring systems by presenting all your data in a more intuitive and impactful manner. Ultimately, our goal is to enhance your data visualization experience, making it simpler and more effective for your organization.

Google Cloud Bigtable provides a fully managed, scalable NoSQL data service that can handle large operational and analytical workloads. Cloud Bigtable is fast and performant. It's the storage engine that grows with your data, from your first gigabyte up to a petabyte-scale for low latency applications and high-throughput data analysis. Seamless scaling and replicating: You can start with one cluster node and scale up to hundreds of nodes to support peak demand. Replication adds high availability and workload isolation to live-serving apps. Integrated and simple: Fully managed service that easily integrates with big data tools such as Dataflow, Hadoop, and Dataproc. Development teams will find it easy to get started with the support for the open-source HBase API standard.

Historian is a software solution designed for the comprehensive and ongoing tracking of various metrics. It utilizes an InfluxDB time-series database to facilitate long-term monitoring applications seamlessly. You can oversee data related to vibration, temperature, inclination, strain, pressure, and more, using either a self-hosted setup or a completely managed cloud service. The system is compatible with the standard OPC UA protocol, ensuring efficient data access and enabling integration with DewesoftX data acquisition software, SCADAs, ERPs, or any other OPC UA-enabled clients. The data is securely housed within a cutting-edge open-source InfluxDB database, which is crafted by InfluxData and written in Go, allowing for rapid and high-availability storage and retrieval of time series data relevant to operational monitoring, application metrics, IoT sensor data, and real-time analytics. Users can choose to install the Historian service either locally on the measurement unit or within their local intranet, or opt for a fully managed cloud service tailored to their needs. This flexibility makes Historian a versatile choice for organizations looking to enhance their data monitoring capabilities.

Data plays a crucial role in every facet of a processing plant or facility, serving as the backbone for most operational workflows, critical business decisions, and various environmental occurrences. Often, failures can be linked back to this very data, manifesting as operator mistakes, faulty sensors, safety incidents, or inadequate analytics. APERIO steps in to address these challenges effectively. In the realm of Industry 4.0, data integrity stands as a vital component, forming the bedrock for more sophisticated applications, including predictive models, process optimization, and tailored AI solutions. Recognized as the premier provider of dependable and trustworthy data, APERIO DataWise enables organizations to automate the quality assurance of their PI data or digital twins on a continuous and large scale. By guaranteeing validated data throughout the enterprise, businesses can enhance asset reliability significantly. Furthermore, this empowers operators to make informed decisions, fortifies the detection of threats to operational data, and ensures resilience in operations. Additionally, APERIO facilitates precise monitoring and reporting of sustainability metrics, promoting greater accountability and transparency within industrial practices.

Observo AI is an innovative platform tailored for managing large-scale telemetry data within security and DevOps environments. Utilizing advanced machine learning techniques and agentic AI, it automates the optimization of data, allowing companies to handle AI-generated information in a manner that is not only more efficient but also secure and budget-friendly. The platform claims to cut data processing expenses by over 50%, while improving incident response speeds by upwards of 40%. Among its capabilities are smart data deduplication and compression, real-time anomaly detection, and the intelligent routing of data to suitable storage or analytical tools. Additionally, it enhances data streams with contextual insights, which boosts the accuracy of threat detection and helps reduce the occurrence of false positives. Observo AI also features a cloud-based searchable data lake that streamlines data storage and retrieval, making it easier for organizations to access critical information when needed. This comprehensive approach ensures that enterprises can keep pace with the evolving landscape of cybersecurity threats.