Best Data Management Software for Linux of 2025 - Page 9

Noction Flow Analyzer is a network monitoring, alerting, and analytics tool that can ingest NetFlow, IPFIX and sFlow data. Engineers can use the NetFlow analyzer to optimize their network and applications performance, control bandwidth usage, plan network capacity, monitor and alert, perform detailed BGP peering analysis and improve security.

Polymer DLP secures your SaaS apps by preventing sensitive information like business-critical data or PII from being sent to the wrong people. We used machine learning and natural language processing to automatically detect and remediate files and messages in real time. In addition we provide training at the time of infraction, which is proven to help prevent future incidents before they happen. Try for free and set up your custom policy in minutes. Polymer is constantly expanding, currently we integrate with Slack, Google Drive, Microsoft Teams, One Drive, Bitbucket, Github and Box.

Faros AI combines all your operational data from multiple sources and enhances them with machine learning signals. The Faros AI Engineering Operations Platform allows you to harness this data so you can accelerate productivity, and better manager your engineering operations. With Faros AI, engineering leaders can scale their operations in a more data-informed way — using data to identify bottlenecks, measure progress towards organizational goals, better support teams with the right resources, and accurately assess the impact of interventions over time. DORA Metrics come standard in Faros AI, and the platform is extensible to allow organizations to build their own custom dashboards and metrics so they can get deep insights into their engineering operations and take intelligent action in a data-driven manner. Leading organizations including Box, Coursera, GoFundMe, Astronomer, Salesforce, etc. trust Faros AI as their engops platform of choice.

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/

One area that has not benefited as much from DevOps is the database change process. It is time to bring CI/CD into the database. In the last few years, application release technology has advanced significantly. It used to take weeks, if not months, to release new software. Organizations have changed their workflows and processes so that it takes just days or even hours to release new software. Every software project must perform database schema migrations. There are many reasons why database updates are necessary. New features may require the addition of new attributes to existing tables, or completely new tables. Bug fixes can lead to changes in the names and data types of the database. Additional indexes may be required to address performance issues. Manual rework is still common in DevOps-adopted organizations when it comes to stored procedure and database schema changes.

Graphlytic is a web-based BI platform that allows knowledge graph visualization and analysis. Interactively explore the graph and look for patterns using the Cypher query language or query templates for non-technical users. Users can also use filters to find answers to any graph question. The graph visualization provides deep insights into industries such as scientific research and anti-fraud investigation. Even users with little knowledge of graph theory can quickly explore the data. Cytoscape.js allows graph rendering. It can render tens to thousands of nodes and hundreds upon thousands of relationships. The application is available in three formats: Desktop, Cloud, or Server. Graphlytic Desktop is a Neo4j Desktop app that can be installed in just a few mouse clicks. Cloud instances are great for small teams who don't want or need to worry about installing and need to be up and running quickly.

VelocityDB stands out as a unique database engine, renowned for its ability to store data more quickly and efficiently than any competing solutions while being significantly more affordable. Unlike traditional databases that rely on mapping to tables, JSON, or XML, it retains .NET objects in their native format. Complementing this is VelocityGraph, an open-source property graph database that seamlessly integrates with the VelocityDB object database. As a C# .NET noSQL object database, VelocityDB is enhanced by VelocityGraph, making it one of the fastest, most scalable, and flexible database options available today. Bugs that are reported along with reproducible test cases are typically resolved within a week, showcasing the responsiveness of the development team. The primary advantage of using this database system lies in its remarkable flexibility, enabling developers to tailor their applications to meet even the most specific requirements. With VelocityDB, you have the freedom to select the most suitable data structures for your needs, granting you control over the persistent placement of data, as well as how it is indexed and accessed. This level of customization sets VelocityDB apart in the realm of database technology.

InfiniteGraph is a massively scalable graph database specifically designed to excel at high-speed ingest of massive volumes of data (billions of nodes and edges per hour) while supporting complex queries. InfiniteGraph can seamlessly distribute connected graph data across a global enterprise. InfiniteGraph is a schema-based graph database that supports highly complex data models. It also has an advanced schema evolution capability that allows you to modify and evolve the schema of an existing database. InfiniteGraph’s Placement Management Capability allows you to optimize the placement of data items resulting in tremendous performance improvements in both query and ingest. InfiniteGraph has client-side caching which caches frequently used node and edges. This can allow InfiniteGraph to perform like an in-memory graph database. InfiniteGraph's DO query language enables complex "beyond graph" queries not supported by other graph databases.

OrigoDB allows you to create high-quality, mission-critical systems that deliver real-time performance while significantly reducing time and costs. This is not just empty advertising! We encourage you to continue reading for a straightforward overview of our features. Feel free to reach out with any inquiries or download and give it a try today! Operations performed in memory are significantly quicker than those conducted on disk. An individual OrigoDB engine is capable of processing millions of read transactions and thousands of write transactions per second, all while ensuring synchronous command journaling to a local SSD. This capability is the primary motivation behind the development of OrigoDB. Utilizing a single object-oriented domain model is much more efficient than managing an entire stack that encompasses a relational model, object/relational mapping, data access code, views, and stored procedures, which can lead to unnecessary complexity! Furthermore, the OrigoDB engine provides complete ACID compliance right from the start. Commands are executed sequentially, allowing the in-memory model to transition smoothly from one consistent state to another, ensuring data integrity at all times. This streamlined approach ultimately enhances overall system performance and reliability.

Enterprise Recon by Ground Labs is a leading, award-winning solution that empowers organizations to confidently discover, manage, and remediate sensitive personal data across their entire digital estate—from legacy systems to the modern cloud. Our technology provides the unparalleled visibility needed to reduce risk, simplify compliance, and maintain a strong security posture globally. Unmatched Discovery and Accuracy Powered by GLASS™ At the core of Enterprise Recon is GLASS Technology™, Ground Labs' proprietary pattern-matching engine. This is a crucial differentiator, designed specifically for data discovery: Fastest and Most Accurate: GLASS Technology™ allows Enterprise Recon to deliver the fastest and most accurate sensitive data discovery on the market, dramatically minimizing system overheads and the most common complaint in the industry: false positives. Deep Search Capabilities: It performs sophisticated, deep searches for over 300 pre-configured, out-of-the-box data types across various formats, including databases, documents, emails, compressed files, and even in-memory data, ensuring no sensitive asset is missed. Customization: Enables complete customisation of sensitive data types, enabling organizations to search for proprietary or highly-specific data patterns unique to their business or industry. Comprehensive Platform and Deployment Coverage Enterprise Recon is engineered for the complex, heterogeneous environments of the modern enterprise, offering unparalleled breadth in platform support: Broad OS Support: Supports sensitive data discovery on an extensive range of operating systems, including common platforms like Windows, macOS, and Linux, as well as legacy and specialized systems such as FreeBSD, Solaris and AIX

IRI FieldShield® is a powerful and affordable data discovery and de-identification package for masking PII, PHI, PAN and other sensitive data in structured and semi-structured sources. Front-ended in a free Eclipse-based design environment, FieldShield jobs classify, profile, scan, and de-identify data at rest (static masking). Use the FieldShield SDK or proxy-based application to secure data in motion (dynamic data masking). The usual method for masking RDB and other flat files (CSV, Excel, LDIF, COBOL, etc.) is to classify it centrally, search for it globally, and automatically mask it in a consistent way using encryption, pseudonymization, redaction or other functions to preserve realism and referential integrity in production or test environments. Use FieldShield to make test data, nullify breaches, or comply with GDPR. HIPAA. PCI, PDPA, PCI-DSS and other laws. Audit through machine- and human-readable search reports, job logs and re-ID risks scores. Optionally mask data when you map it; FieldShield functions can also run in IRI Voracity ETL and federation, migration, replication, subsetting, and analytic jobs. To mask DB clones run FieldShield in Windocks, Actifio or Commvault. Call it from CI/CD pipelines and apps.

Scanbot SDK offers a B2B product called the Scanbot Software Developer Kit (SDK). This allows enterprises to integrate data capture capabilities such barcode scanning, document detection and scanning, as well as data extraction functions into their mobile (iOS/Android) and web applications. The Scanbot SDK works only on the device and is 100% offline. It will not send data to any other server than yours. Scanbot also offers encryption and other features to ensure that data is only shared between you and your server at rest and in transit. The SDK can be integrated in less than a week and is compatible with most web- and app-based development platforms. Industry-leading firms like AXA, Generali, Deutsche Telekom, and ArcBest already rely on Scanbot SDK. You can either try them in our demo app (available on the App and Play Store), or you can start testing it in your app already - with a complimentary trial license code available on this website.

AD360 is an integrated identity management (IAM), solution that manages user identities, controls access to resources, enforces security, and ensures compliance. AD360 allows you to perform all your IAM tasks using a simple and easy-to-use interface. All these functions are available for Windows Active Directory, Exchange Servers and Office 365. You can choose the modules that you need and get started addressing IAM issues across hybrid, on-premises, and cloud environments with AD360. You can easily provision, modify, and deprovision mailboxes and accounts for multiple users from one console. This includes Exchange servers, Office 365, G Suite, and Office 365. To bulk provision user accounts, you can use customizable templates for user creation and import data from CSV.

DSVMs, or Data Science Virtual Machines, are pre-configured Azure Virtual Machine images equipped with a variety of widely-used tools for data analysis, machine learning, and AI training. They ensure a uniform setup across teams, encouraging seamless collaboration and sharing of resources while leveraging Azure's scalability and management features. Offering a near-zero setup experience, these VMs provide a fully cloud-based desktop environment tailored for data science applications. They facilitate rapid and low-friction deployment suitable for both classroom settings and online learning environments. Users can execute analytics tasks on diverse Azure hardware configurations, benefiting from both vertical and horizontal scaling options. Moreover, the pricing structure allows individuals to pay only for the resources they utilize, ensuring cost-effectiveness. With readily available GPU clusters that come pre-configured for deep learning tasks, users can hit the ground running. Additionally, the VMs include various examples, templates, and sample notebooks crafted or validated by Microsoft, which aids in the smooth onboarding process for numerous tools and capabilities, including but not limited to Neural Networks through frameworks like PyTorch and TensorFlow, as well as data manipulation using R, Python, Julia, and SQL Server. This comprehensive package not only accelerates the learning curve for newcomers but also enhances productivity for seasoned data scientists.

Powerslide is a new data storytelling and visualization tool. This software allows business users to quickly and easily create data usages. Powerslide provides an intuitive and innovative solution to data analysis, visualization, and presentation. Powerslide is interactive and collaborative. It solves data problems in a simple, practical, and design-friendly interface. With a simple, interactive, and efficient platform, you can simplify the analysis and communication process of your data. Powerslide is both intuitive and beautiful. You can create your KPIs or data visualization in just a few mouse clicks. Then, you can stage them through a report or dashboard or an infographic to make it easier to understand. Powerslide is: Designed for business, this interface is intuitive. - A variety of data visualisations - A collaborative mode - Automated updates - Several connectors: CSV, Excel, Denodo, Snowflake, Google Sheets, API Rest, Zapier, Oracle, SQL Server

Senzing® entity resolution API software provides the most advanced, affordable, and easy-to-use data matching and relationship detection capabilities available. With Senzing software, you can automatically resolve records about people, organizations and their relationships in real time as new data is received. The highly accurate and complete views Senzing software delivers allow you to reduce costs and enable new revenue opportunities. Senzing provides a set of libraries that that can be deployed on premises or in the cloud, in a variety of ways, depending on your architecture and environment requirements. Data remains in your ecosystem and never flows to Senzing, Inc. Minimal data preparation is required when and no tuning, training or entity resolution experts are needed. A free proof of concept can be completed in about six hours on AWS or bare metal. You can try the Senzing API on up to 100K records for free.

Datalore is a platform for collaborative data science and analytics that aims to improve the entire analytics workflow and make working with data more enjoyable for both data scientists as well as data-savvy business teams. Datalore is a collaborative platform that focuses on data teams workflow. It offers technical-savvy business users the opportunity to work with data teams using no-code and low-code, as well as the power of Jupyter Notebooks. Datalore allows business users to perform analytic self-service. They can work with data using SQL or no-code cells, create reports, and dive deep into data. It allows core data teams to focus on simpler tasks. Datalore allows data scientists and analysts to share their results with ML Engineers. You can share your code with ML Engineers on powerful CPUs and GPUs, and you can collaborate with your colleagues in real time.

Navicat Data Modeler is an efficient and budget-friendly tool for database design that enables users to create high-quality conceptual, logical, and physical data models. It provides a visual interface for designing database structures, facilitates both reverse and forward engineering, allows for the importation of models from ODBC data sources, and can generate intricate SQL/DDL statements while offering the ability to print models. This tool simplifies the process of developing complex entity relationship models, enabling users to generate SQL scripts with just a click. Supporting a variety of database systems such as MySQL, MariaDB, Oracle, SQL Server, PostgreSQL, and SQLite, it allows for the creation, modification, and design of models through professional object designers tailored for Tables and Views. Users can manage their tasks effectively without the need to write intricate SQL for object creation and editing, providing clarity on their work. Furthermore, Navicat Data Modeler accommodates three standard notations, including Crow’s Foot, IDEF1x, and UML, making it versatile for different design preferences. With its comprehensive features, it stands out as an indispensable tool for both novice and experienced database designers.

Facilitates faster and more straightforward creation and alteration of databases, making routine database tasks more efficient. It supports a variety of operating systems and database types under a single license. Users can apply changes using generated scripts and utilize ER diagrams for modeling, analyzing, and conveying their designs effectively. The software allows for quick reverse engineering of databases into the database designer within seconds. Our main focus is on developing features that enhance the productivity of database developers during design processes. By employing rigorous testing and maintaining continuous release cycles, we aim to create a dependable product for users. DbWrench is compatible with Windows, Mac OS X, and Linux, all covered under a single license, and works seamlessly with today's leading database systems. Users can directly edit database elements in the diagram, eliminating the need to navigate through tree nodes and property sheets. Additionally, it offers multiple ER notation options, including Bachman, Barker, and Information Engineering, to cater to various user preferences. This flexibility ensures that users have the tools they need to create effective database designs efficiently.

Easily create and modify database models through a user-friendly interface that simplifies the process. The forms clearly indicate which fields are mandatory for accurate SQL code generation. You are free to obtain, alter, and share the source code at no cost. This project features a public repository offering full access and the ability to fork the code, enabling developers to craft their own variations based on the original. Built on the Qt framework, pgModeler is compatible with Windows, Linux, and macOS, and its build scripts can be easily adjusted to address specific dependencies unique to each operating system. You can design a model once and export it across various versions effortlessly. With its dynamic code generation capabilities, pgModeler supports exporting to multiple PostgreSQL versions, ranging from 9.x to 13.x. If you find that certain features are lacking, you can utilize the plug-in development interface to create custom extensions for pgModeler without altering the core code. Moreover, this flexibility allows developers to enhance their database modeling experience and tailor it to their specific needs.

Riak®, TS is an enterprise-grade NoSQL Time Series Database that is specifically designed for IoT data and Time Series data. It can ingest, transform, store, and analyze massive amounts of time series information. Riak TS is designed to be faster than Cassandra. Riak TS masterless architecture can read and write data regardless of network partitions or hardware failures. Data is evenly distributed throughout the Riak ring. By default, there are three copies of your data. This ensures that at least one copy is available for reading operations. Riak TS is a distributed software system that does not have a central coordinator. It is simple to set up and use. It is easy to add or remove nodes from a cluster thanks to the masterless architecture. Riak TS's masterless architecture makes it easy for you to add or remove nodes from your cluster. Adding nodes made of commodity hardware to your cluster can help you achieve predictable and almost linear scale.

SiriDB is optimized for speed. Inserts and queries are answered quickly. You can speed up your development with the custom query language. SiriDB is flexible and can be scaled on the fly. There is no downtime when you update or expand your database. You can scale your database without losing speed. As we distribute your time series data across all pools, we make full use of all resources. SiriDB was designed to deliver unmatched performance with minimal downtime. A SiriDB cluster distributes time series across multiple pools. Each pool has active replicas that can be used for load balancing or redundancy. The database can still be accessed even if one of the replicas is unavailable.

Coder offers self-hosted cloud development environments, provisioned as code and ready for developers from day one. Favored by enterprises, Coder is open source and can be deployed air-gapped on-premise or in your cloud, ensuring powerful infrastructure access without sacrificing governance. By shifting local development and source code to a centralized infrastructure, Coder allows developers to access their remote environments via their preferred desktop or web-based IDE. This approach enhances developer experience, productivity, and security. With Coder’s ephemeral development environments, provisioned as code from pre-defined templates, developers can instantly create new workspaces. This streamlines the process, eliminating the need to deal with local dependency versioning issues or lengthy security approvals. Coder enables developers to onboard or switch projects in a matter of minutes.

Dataplane's goal is to make it faster and easier to create a data mesh. It has robust data pipelines and automated workflows that can be used by businesses and teams of any size. Dataplane is more user-friendly and places a greater emphasis on performance, security, resilience, and scaling.

It is available at no cost for everyone and can be utilized for any purpose, including commercial uses. The safety of the application is ensured as its source code is open for public review. The SQL Editor interface offers assistance with SQL syntax through hints and highlighting features, allows for formatted code display, and identifies syntax errors for users. By using Ctrl+click on tables mentioned in SQL queries, users can easily access those tables, indexes, triggers, or views. Additionally, it supports executing SQL statements that span multiple databases within a single query due to its built-in transparent database attachment feature. Users can also create custom collation sequences, which are algorithms for comparing values that can be utilized in clauses like ORDER BY. Furthermore, it comes in a portable version, meaning users can simply download, unzip, and run it without needing to install or acquire administrative privileges, making it convenient to use on various systems. This exceptional accessibility and user-friendly design contribute to its widespread popularity among developers and database administrators alike.