Best Data Management Software for CrateDB

Gain, generate, and analyze business data and meaningful insights with Tableau, an integrated business intelligence (BI) and analytics solution. With Tableau, users are able to collect data from different sources such as spreadsheets, SQL databases, Salesforce, and cloud apps. Tableau provides users with real-time visual analytics and interactive dashboard that enables them to slice and dice datasets for making relevant insights and look for new opportunities. Tableau also allows users to customize the platform to serve different kinds of industry verticals like banking, communication, and more.

Free multi-platform database tool for developers, database administrators, analysts and all people who need to work with databases. Supports all popular databases: MySQL, PostgreSQL, SQLite, Oracle, DB2, SQL Server, Sybase, MS Access, Teradata, Firebird, Apache Hive, Phoenix, Presto, etc. Copy As: format configuration editor was added. Extra configuration for filter dialog (performance). Sort by column as fixed (for small fetch sizes). Case-insensitive filters support was added. Plaintext view now support top/bottom dividers. Data editor was fixed (when column name conflicts with alias name). Duplicate row(s) command was fixed for multiple selected rows. Edit sub-menu was returned to the context menu. Columns auto-size configuration was added. Dictionary viewer was fixed (for read-only connections). Current/selected row highlighting support was added (configurable).

DataClarity Unlimited Analytics is the only free modern embeddable data and analytics platform in the world that provides a self-service, powerful, secure and seamless end-to-end experience. Highlights: SIMPLIFIED DATA INTEGRATION – Easily connect, join, curate, cache and catalog diverse data through drag and drop, custom SQL builder & AI-powered data profiling. | INTERACTIVE DASHBOARDS – craft compelling reports using 80 stunning visualizations, geospatial maps and flexibility to bring your own charts. | REAL-TIME ANALYSIS – Perform advanced analysis & data exploration using drill-down, drill-through, filters, built-in statistical & predictive models, or your own Python and R code. | SEAMLESS APPLICATION INTEGRATION – Achieve smooth integration with versatile APIs, tailor-made configurations & flexible embedding features. | SECURITY & GOVERNANCE – Ensure adherence to your security guidelines, governance standards, multitenancy, row-level data protection, and Single Sign-On (SSO).

Apache Kafka® is an open-source, distributed streaming platform. Scale production clusters up to a thousand brokers, trillions of messages per day, petabytes of data, hundreds of thousands of partitions. Elastically expand and contract storage and processing. Stretch clusters efficiently over availability zones or connect separate clusters across geographic regions. Process streams of events with joins, aggregations, filters, transformations, and more, using event-time and exactly-once processing. Kafka’s out-of-the-box Connect interface integrates with hundreds of event sources and event sinks including Postgres, JMS, Elasticsearch, AWS S3, and more. Read, write, and process streams of events in a vast array of programming languages.

StreamSets DataOps Platform. The data integration platform to build, run, monitor and manage smart data pipelines that deliver continuous data for DataOps, and power modern analytics and hybrid integration. Only StreamSets provides a single design experience for all design patterns for 10x greater developer productivity; smart data pipelines that are resilient to change for 80% less breakages; and a single pane of glass for managing and monitoring all pipelines across hybrid and cloud architectures to eliminate blind spots and control gaps. With StreamSets, you can deliver the continuous data that drives the connected enterprise.

Telegraf is the open source server agent to help you collect metrics from your stacks, sensors and systems. Telegraf is a plugin-driven server agent for collecting and sending metrics and events from databases, systems, and IoT sensors. Telegraf is written in Go and compiles into a single binary with no external dependencies, and requires a very minimal memory footprint. Telegraf can collect metrics from a wide array of inputs and write them into a wide array of outputs. It is plugin-driven for both collection and output of data so it is easily extendable. It is written in Go, which means that it is a compiled and standalone binary that can be executed on any system with no need for external dependencies, no npm, pip, gem, or other package management tools required. With 300+ plugins already written by subject matter experts on the data in the community, it is easy to start collecting metrics from your end-points.

Cluvio is the #1 cloud analytics platform for startups and data-driven teams, trusted by over 1800 companies like yours. Use SQL and R to analyze your data and create beautiful, interactive dashboards for your entire company in few minutes. There is a wealth of information hiding in the data in your database just waiting to be discovered. See your most important KPIs on interactive, real-time dashboards anywhere, anytime. Receive alerts for conditions that you define, a sudden drop in a number of orders, increased error rates or achieved revenue goals. Defining and exposing reality based on actual data makes everyone in your company more curious and engaged in your company’s success. Write SQL, get charts, share dashboards. You won’t find an easier tool than Cluvio. You can easily make dashboards in Cluvio interactive with time-based and custom filters. Cluvio dashboards are a pleasure to look at and easy to use.

Power your metrics and alerting with a leading open-source monitoring solution. Prometheus fundamentally stores all data as time series: streams of timestamped values belonging to the same metric and the same set of labeled dimensions. Besides stored time series, Prometheus may generate temporary derived time series as the result of queries. Prometheus provides a functional query language called PromQL (Prometheus Query Language) that lets the user select and aggregate time series data in real time. The result of an expression can either be shown as a graph, viewed as tabular data in Prometheus's expression browser, or consumed by external systems via the HTTP API. Prometheus is configured via command-line flags and a configuration file. While the command-line flags configure immutable system parameters (such as storage locations, amount of data to keep on disk and in memory, etc.). Download: https://sourceforge.net/projects/prometheus.mirror/

Meet the easy, open source way for everyone in your company to ask questions and learn from data. Connect to your data and get it in front of your team. Dashboards (like this one) are easy to build, share, and explore. Anyone on your team can get answers to questions about your data with just a few clicks, whether it's the CEO or Customer Support. When the questions get more complicated, SQL and our notebook editor are there for the data savvy. Visual joins, multiple aggregations and filtering steps give you the tools to dig deeper into your data. Add variables to your queries to create interactive visualizations that users can tweak and explore. Set up alerts and scheduled reports to get the right data in front of the right people at the right time. Start in a couple clicks with the hosted version, or use Docker to get up and running on your own for free. Connect to your existing data, invite your team, and you have a BI solution that would usually take a sales call.

PostgreSQL is a powerful, open-source object-relational database system with over 30 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance. There is a wealth of information to be found describing how to install and use PostgreSQL through the official documentation. The open-source community provides many helpful places to become familiar with PostgreSQL, discover how it works, and find career opportunities. Learm more on how to engage with the community. The PostgreSQL Global Development Group has released an update to all supported versions of PostgreSQL, including 15.1, 14.6, 13.9, 12.13, 11.18, and 10.23. This release fixes 25 bugs reported over the last several months. This is the final release of PostgreSQL 10. PostgreSQL 10 will no longer receive security and bug fixes. If you are running PostgreSQL 10 in a production environment, we suggest that you make plans to upgrade.

Observe all of your data in one place with Enterprise plugins like Splunk, ServiceNow, Datadog, and more. Built-in collaboration features allow teams to work together from a single dashboard. Advanced security and compliance features to ensure your data is always secure. Access to Prometheus, Graphite, Grafana experts and hands-on support teams. Other vendors will try to sell you an “everything in my database” mentality. At Grafana Labs, we have a different approach: We want to help you with your observability, not own it. Grafana Enterprise includes access to enterprise plugins that take your existing data sources and allow you to drop them right into Grafana. This means you can get the best out of your complex, expensive monitoring solutions and databases by visualizing all the data in an easier and more effective way.

Superset is fast, lightweight, intuitive, and loaded with options that make it easy for users of all skill sets to explore and visualize their data, from simple line charts to highly detailed geospatial charts. Superset can connect to any SQL based datasource through SQLAlchemy, including modern cloud native databases and engines at petabyte scale. Superset is lightweight and highly scalable, leveraging the power of your existing data infrastructure without requiring yet another ingestion layer.

An easy to use, powerful, and reliable system to process and distribute data. Apache NiFi supports powerful and scalable directed graphs of data routing, transformation, and system mediation logic. Some of the high-level capabilities and objectives of Apache NiFi include web-based user interface, offering a seamless experience between design, control, feedback, and monitoring. Highly configurable, loss tolerant, low latency, high throughput, and dynamic prioritization. Flow can be modified at runtime, back pressure, data provenance, track dataflow from beginning to end, designed for extension. Build your own processors and more. Enables rapid development and effective testing. Secure, SSL, SSH, HTTPS, encrypted content, and much more. Multi-tenant authorization and internal authorization/policy management. NiFi is comprised of a number of web applications (web UI, web API, documentation, custom UI's, etc). So, you'll need to set up your mapping to the root path.

Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows.