Best Data Management Software in the UK - Page 99
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Compare the Top Data Management Software in the UK as of June 2026 - Page 99
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InfiniDB
Database of Databases
InfiniDB is a column-store DBMS optimized for OLAP workloads. It has a distributed architecture to support Massive Paralllel Processing (MPP). It uses MySQL as its front-end such that users familiar with MySQL can quickly migrate to InfiniDB. Due to this fact, users can connect to InfiniDB using any MySQL connector. InfiniDB applies MVCC to do concurrency control. It uses term System Change Number (SCN) to indicate a version of the system. In its Block Resolution Manager (BRM), it utilizes three structures, version buffer, version substitution structure, and version buffer block manager, to manage multiple versions. InfiniDB applies deadlock detection to resolve conflicts. InfiniDB uses MySQL as its front-end and supports all MySQL syntaxes, including foreign keys. InfiniDB is a columnar DBMS. For each column, InfiniDB applies range partitioning and stores the minimum and maximum value of each partition in a small structure called extent map. -
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qikkDB
qikkDB
QikkDB is a GPU accelerated columnar database, delivering stellar performance for complex polygon operations and big data analytics. When you count your data in billions and want to see real-time results you need qikkDB. We support Windows and Linux operating systems. We use Google Tests as the testing framework. There are hundreds of unit tests and tens of integration tests in the project. For development on Windows, Microsoft Visual Studio 2019 is recommended, and its dependencies are CUDA version 10.2 minimal, CMake 3.15 or newer, vcpkg, boost. For development on Linux, the dependencies are CUDA version 10.2 minimal, CMake 3.15 or newer, and boost. This project is licensed under the Apache License, Version 2.0. You can use an installation script or dockerfile to install qikkDB. -
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Oracle Autonomous Data Warehouse is a cloud data warehouse service that eliminates all the complexities of operating a data warehouse, dw cloud, data warehouse center, securing data, and developing data-driven applications. It automates provisioning, configuring, securing, tuning, scaling, and backing up of the data warehouse. It includes tools for self-service data loading, data transformations, business models, automatic insights, and built-in converged database capabilities that enable simpler queries across multiple data types and machine learning analysis. It’s available in both the Oracle public cloud and customers' data centers with Oracle Cloud@Customer. Detailed analysis by industry expert DSC illustrates why Oracle Autonomous Data Warehouse is a better pick for the majority of global organizations. Learn about applications and tools that are compatible with Autonomous Data Warehouse.
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Apache Pinot
Apache Corporation
Pinot is designed to answer OLAP queries with low latency on immutable data. Pluggable indexing technologies - Sorted Index, Bitmap Index, Inverted Index. Joins are currently not supported, but this problem can be overcome by using Trino or PrestoDB for querying. SQL like language that supports selection, aggregation, filtering, group by, order by, distinct queries on data. Consist of of both offline and real-time table. Use real-time table only to cover segments for which offline data may not be available yet. Detect the right anomalies by customizing anomaly detect flow and notification flow. -
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Apache Hudi
Apache Corporation
Hudi is a rich platform to build streaming data lakes with incremental data pipelines on a self-managing database layer, while being optimized for lake engines and regular batch processing. Hudi maintains a timeline of all actions performed on the table at different instants of time that helps provide instantaneous views of the table, while also efficiently supporting retrieval of data in the order of arrival. A Hudi instant consists of the following components. Hudi provides efficient upserts, by mapping a given hoodie key consistently to a file id, via an indexing mechanism. This mapping between record key and file group/file id, never changes once the first version of a record has been written to a file. In short, the mapped file group contains all versions of a group of records. -
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DuckDB
DuckDB
Processing and storing tabular datasets, e.g. from CSV or Parquet files. Large result set transfer to client. Large client/server installations for centralized enterprise data warehousing. Writing to a single database from multiple concurrent processes. DuckDB is a relational database management system (RDBMS). That means it is a system for managing data stored in relations. A relation is essentially a mathematical term for a table. Each table is a named collection of rows. Each row of a given table has the same set of named columns, and each column is of a specific data type. Tables themselves are stored inside schemas, and a collection of schemas constitutes the entire database that you can access. -
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Typo
Typo
TYPO is a data quality solution that provides error correction at the point of entry into information systems. Unlike reactive data quality tools that attempt to resolve data errors after they are saved, Typo uses AI to proactively detect errors in real-time at the initial point of entry. This enables immediate correction of errors prior to storage and propagation into downstream systems and reports. Typo can be used on web applications, mobile apps, devices and data integration tools. Typo inspects data in motion as it enters your enterprise or at rest after storage. Typo provides comprehensive oversight of data origins and points of entry into information systems including devices, APIs and application users. When an error is identified, the user is notified and given the opportunity to correct the error. Typo uses machine learning algorithms to detect errors. Implementation and maintenance of data rules is not necessary. -
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Canoe
Canoe Intelligence
First-of-its-kind AI technology powering the future of alternative investments. Canoe has reimagined the future of alternative investments with cloud-based, machine learning technology for document collection, data extraction and data science initiatives. We transform complex documents into actionable intelligence within seconds, and empower allocators with tools to unlock new efficiencies for their business. Systematically and consistently categorize, rename, and store documents in our cloud-based repository. Leverage AI and machine-learning based collective intelligence to identify, extract, and normalize data. Action hundreds of accounting, business and investment rules to ensure data accuracy. Seamlessly deliver data to any downstream system via API or compatible flat-file formats. Since 2013, our team of industry experts has been building and perfecting Canoe’s technology to transform the way alternative investors and allocators like you can access your data. -
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Staple
Staple AI
Staple AI is a compliance infrastructure for AI-powered document flows. The first mile of document processing. Enterprises processing documents at scale face a growing compliance problem: AI extracts data, but can't prove where it came from. Staple AI fixes that. Every extracted field carries a cryptographic chain of custody through the MSD (Metastructured Data) layer, from the source document to the ERP entry. Auditors get answers. Boards get accountability. Regulators get evidence. Built at the intersection of Artificial Intelligence (AI), Machine Learning, analytics, and enterprise-grade document infrastructure. What Staple AI does: Intelligent Document Processing across invoices, POs, GRNs, bank statements, KYC docs, contracts, payslips, claims, delivery orders, and more. Template-free. Self-learning. 95%+ extraction accuracy. n-Way Document Matching up to 10 document types simultaneously at the line-item level, with fuzzy matching and variance thresholds. -
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ThreadDB
Textile
ThreadDB is a multi-party database built on IPFS and Libp2p that provides an alternative architecture for data on the web. ThreadDB aims to help power a new generation of web technologies by combining a novel use of event sourcing, Interplanetary Linked Data (IPLD), and access control to provide a distributed, scalable, and flexible database solution for decentralized applications. There are two implementations of ThreadDB, the first is written in Go. The second implementation is written in JavaScript (Typescript, really). This implementation has some optimizations to make it more ideal when writing web applications. The JavaScript implementation is currently a Client of the Go implementation. You can run it against your own go-threads instance or connect it to the Textile Hub to use one of ours. In general, when building apps that use threads in a remote context, like the browser, it's best to push the networking later to remote services whenever possible. -
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KX Insights
KX
KX Insights is a cloud-native platform for critical real-time performance and continuous actionable intelligence. Using complex event processing, high-speed analytics and machine learning interfaces, it enables fast decision-making and automated responses to events in fractions of a second. It’s not just storage and compute elasticity that have moved to the cloud. It’s everything: data, tools, development, security, connectivity, operations, maintenance. KX can help you leverage that power to make smarter, more insightful decisions by integrating real-time analytics into your business operations. KX Insights leverages industry standards to ensure openness and interoperability with other technologies in order to deliver insights faster and more cost-effectively. It operates a microservices-based architecture for capturing, storing and processing high-volume, high-velocity data using cloud standards, services, and protocols. -
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KX Streaming Analytics provides the ability to ingest, store, process, and analyze historic and time series data to make analytics, insights, and visualizations instantly available. To help ensure your applications and users are productive quickly, the platform provides the full lifecycle of data services, including query processing, tiering, migration, archiving, data protection, and scaling. Our advanced analytics and visualization tools, used widely across finance and industry, enable you to define and perform queries, calculations, aggregations, machine learning and AI on any streaming and historical data. Deployable across multiple hardware environments, data can come from real-time business events and high-volume sources including sensors, clickstreams, radio-frequency identification, GPS systems, social networking sites, and mobile devices.
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Versio.io
Versio.io
Versio.io is an enterprise software to manage the detection and post-processing of changes in a enterprise company. Our unique and innovative approaches have enabled us to build a completely new kind of enterprise product. Below we give you insights into our research and development work. Relationships can exist between assets & configurations. These represent an important extension of information. The original data sources only partially have this information. In Versio.io, we can use the topology service to automatically recognise and map such relationships. This means that relationships or dependencies between instances from any data source can be mapped. All business-relevant assets and configuration items from all levels of an organisation can be captured, historicised, topologised and stored in a central repository. -
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OneTick
OneMarketData
It's performance, superior features and unmatched functionality have led OneTick Database to be embraced by leading banks, brokerages, data vendors, exchanges, hedge funds, market makers and mutual funds. OneTick is the premier enterprise-wide solution for tick data capture, streaming analytics, data management and research. With its superior features and unmatched functionality, OneTick is being embraced enthusiastically by leading hedge funds, mutual funds, banks, brokerages, market makers, data vendors and exchanges. OneTick’s proprietary time series database is a unified, multi-asset class platform that includes a fully integrated streaming analytics engine and built-in business logic to eliminate the need for multiple disparate systems. The system provides the lowest total cost of ownership available. -
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OpenTSDB
OpenTSDB
OpenTSDB consists of a Time Series Daemon (TSD) as well as set of command line utilities. Interaction with OpenTSDB is primarily achieved by running one or more of the independent TSDs. There is no master, no shared state so you can run as many TSDs as required to handle any load you throw at it. Each TSD uses the open source database HBase or hosted Google Bigtable service to store and retrieve time-series data. The data schema is highly optimized for fast aggregations of similar time series to minimize storage space. Users of the TSD never need to access the underlying store directly. You can communicate with the TSD via a simple telnet-style protocol, an HTTP API or a simple built-in GUI. The first step in using OpenTSDB is to send time series data to the TSDs. A number of tools exist to pull data from various sources into OpenTSDB. -
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Machbase
Machbase
Machbase, a time-series database that stores and analyzes a lot of sensor data from various facilities in real time, is the only DBMS solution that can process and analyze big data at high speed. Experience the amazing speed of Machbase! It is the most innovative product that enables real-time processing, storage, and analysis of sensor data. High speed sensor data storage and inquiry for sensor data by embedding DBMS in an Edge devices. Best data storage and extraction performance by DBMS running in a single server. Configuring Multi-node cluster with the advantages of availability and scalability. Total management solution of Edge computing for device, connectivity and data. -
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Blueflood
Blueflood
Blueflood is a high throughput, low latency, multi-tenant distributed metric processing system behind Rackspace Metrics, which is currently used in production by the Rackspace Monitoring team and Rackspace public cloud team to store metrics generated by their systems. In addition to Rackspace metrics, other large scale deployments of Blueflood can be found at community Wiki. Data from Blueflood can be used to construct dashboards, generate reports, graphs or for any other use involving time-series data. It focuses on near-realtime data, with data that is queryable mere milliseconds after ingestion. You send metrics to the ingestion service. You query your metrics from the Query service. And in the background, rollups are batch-processed offline so that queries for large time-periods are returned quickly. -
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RRDtool
RRDtool
RRDtool is the OpenSource industry standard, high performance data logging and graphing system for time series data. RRDtool can be easily integrated in shell scripts, perl, python, ruby, lua or tcl applications. -
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Hawkular Metrics
Hawkular Metrics
Hawkular Metrics is a scalable, asynchronous, multi tenant, long term metrics storage engine that uses Cassandra as the data store and REST as the primary interface. This section provides an overview of some of the key features of Hawkular Metrics. The following sections provide in-depth discussions on these as well as other features. Hawkular Metrics is all about scalability. You can run a single instance backed by a single Cassandra node. You can also scale out Cassandra to multiple nodes to handle increasing loads. The Hawkular Metrics server employs a stateless architecture, which makes it easy to scale out as well. This diagram illustrates the various deployment options made possible with Hawkular Metrics' scalable architecture. The upper left shows the simplest deployment with a single Cassandra node and single Hawkular Metrics node. The bottom right picture shows that it is possible to run more Hawkular Metrics nodes than Cassandra nodes. -
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Heroic
Heroic
Heroic is an open-source monitoring system originally built at Spotify to address problems faced with large scale gathering and near real-time analysis of metrics. Heroic uses a small set of components which are responsible for very specific things. Indefinite retention, as long as you have the hardware spend. Federation support to connect multiple Heroic clusters into a global interface. Heroic uses a small set of components which are responsible for very specific things. Consumers are the component responsible for consuming metrics. When building Heroic it was quickly realized that navigating hundreds of millions of time series without context is hard. Heroic has support for federating requests, which allows multiple independent Heroic clusters to serve clients through a single global interface. This can be used to reduce the amount of geographical traffic by allowing one cluster to operate completely isolated within its zone. -
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Proficy Historian
GE Vernova
Proficy Historian is a best-in-class historian software solution that collects industrial time-series and A&E data at very high speed, stores it efficiently and securely, distributes it, and allows for fast retrieval and analysis —driving greater business value. With decades of experience and thousands of successful customer installations around the world, Proficy Historian changes the way companies perform and compete by making data available for asset and process performance analysis. The most recent Proficy Historian enhances usability, configurability and maintainability with significant architectural improvements. Take advantage of the solution’s simple yet powerful features to unlock new value from your equipment, process data, and business models. Remote collector management with UX. Horizontal scalability that enables enterprise-wide data visibility. -
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Circonus IRONdb
Circonus
Circonus IRONdb makes it easy to handle and store unlimited volumes of telemetry data, easily handling billions of metric streams. Circonus IRONdb enables users to identify areas of opportunity and challenge in real time, providing forensic, predictive, and automated analytics capabilities that no other product can match. Rely on machine learning to automatically set a “new normal” as your data and operations dynamically change. Circonus IRONdb integrates with Grafana, which has native support for our analytics query language. We are also compatible with other visualization apps, such as Graphite-web. Circonus IRONdb keeps your data safe by storing multiple copies of your data in a cluster of IRONdb nodes. System administrators typically manage clustering, often spending significant time maintaining it and keeping it working. Circonus IRONdb allows operators to set and forget their cluster, and stop wasting resources manually managing their time series data store. -
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KairosDB
KairosDB
Data can be pushed in KairosDB via multiple protocols like Telnet, Rest and Graphite. Other mechanisms such as plugins can also be used. KairosDB stores time series in Cassandra, the popular and performant NoSQL datastore. The schema consists of 3 column families. This API provides operations to list existing metric names, list tag names and values, store metric data points, and query for metric data points. With a default install, KairosDB serve up a query page whereby you can query data within the data store. It's designed primarily for development purposes. Aggregators perform an operation on data points and down samples. Standard functions like min, max, sum, count, mean and more are available. Import and export is available on the KairosDB server from the command line. Internal metrics to the data store can monitor the server’s performance. -
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QuestDB
QuestDB
QuestDB is a relational column-oriented database designed for time series and event data. It uses SQL with extensions for time series to assist with real-time analytics. These pages cover core concepts of QuestDB, including setup steps, usage guides, and reference documentation for syntax, APIs and configuration. This section describes the architecture of QuestDB, how it stores and queries data, and introduces features and capabilities unique to the system. Designated timestamp is a core feature that enables time-oriented language capabilities and partitioning. Symbol type makes storing and retrieving repetitive strings efficient. Storage model describes how QuestDB stores records and partitions within tables. Indexes can be used for faster read access on specific columns. Partitions can be used for significant performance benefits on calculations and queries. SQL extensions allow performant time series analysis with a concise syntax. -
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Minitab Connect
Minitab
The best insights are based on the most complete, most accurate, and most timely data. Minitab Connect empowers data users from across the enterprise with self-serve tools to transform diverse data into a governed network of data pipelines, feed analytics initiatives and foster organization-wide collaboration. Users can effortlessly blend and explore data from databases, cloud and on-premise apps, unstructured data, spreadsheets, and more. Flexible, automated workflows accelerate every step of the data integration process, while powerful data preparation and visualization tools help yield transformative insights. Flexible, intuitive data integration tools let users connect and blend data from a variety of internal and external sources, like data warehouses, data lakes, IoT devices, SaaS applications, cloud storage, spreadsheets, and email. -
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DataSentics
DataSentics
Making data science & machine learning have a real impact on organizations. We are an AI product studio, a group of 100 experienced data scientists and data engineers with a combination of experience both from the agile world of digital start-ups as well as major international corporations. We don’t end with nice slides and dashboards. The result that counts is an automated data solution in production integrated inside a real process. We do not report clickers but data scientists and data engineers. We have a strong focus on productionalizing data science solutions in the cloud with high standards of CI and automation. Building the greatest concentration of the smartest and most creative data scientists and engineers by being the most exciting and fulfilling place for them to work in Central Europe. Giving them the freedom to use our critical mass of expertise to find and iterate on the most promising data-driven opportunities, both for our clients and our own products. -
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AXIS Suite
Abaco Systems
Software tools and libraries that help you make your application faster, stronger, and better. Optimized for high performance, graphical user interface to use within application, graphical user interface tool to facilitate application development, GPU focused image processing, general processing, and display and includes an application programming interface for your application. Add visualization and controls to your embedded application in minutes, even with no GUI experience. The most valuable tool you'll ever use to demystify application performance and determinism. Simplified inter-thread communication. Associated GUI to build the application framework and monitor performance. Control how your application maps to hardware. Visualize how the hardware resources are utilized in real-time. Point-to-point data movement/message passing. Graphical user interface tool to facilitate application development. -
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Acodis
Acodis
Intelligent document processing automates the processing of data within documents, contextualizing the document, understanding the information, extracting it, and sending it to the right place. With Acodis, you can do all of this in just a few seconds. The world is full of unstructured data hidden in documents and it will be for a long time to come. That's why we built Acodis so that you can extract data from any document, in any language. Get structured data from any document with machine learning, in seconds. Build and combine document processing workflows with a few clicks, no coding required. Once you capture and automate your document's data, integrate the process into your existing systems. Acodis offers an easy-to-use user interface. This enables your team to automate document-related processes and enables you to make faster decisions based on machine learning. Use the REST client in the programming language that you are using and integrate it with your existing business tools. -
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Retina
Retina
Predict future value from day one. Retina is the customer intelligence solution that provides accurate customer lifetime value metrics early in the customer journey. Optimize marketing budgets in real-time, drive more predictable repeat revenue, and elevate brand equity with the most accurate CLV metrics. Align customer acquisition around CLV with improved targeting, ad relevance, conversion rates & customer loyalty. Build lookalike audiences based on your best customers. Focus on customer behavior instead of demographics. Pinpoint attributes that make leads more likely to convert. Uncover product features that drive valuable customer behavior. Create customer journeys that positively impact lifetime value. Implement changes to boost the value of your customer base. Using a sample of your customer data, Retina delivers individual customer lifetime value calculations to qualified customers before you buy. -
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SylLab
SylLab Systems
SylLab Systems is providing embedded compliance for enterprise data security. Privacy compliance and cybersecurity are expensive and difficult to implement, and many organizations get it wrong. Changes in the architecture, lawyers, consultants are a significant expenditure when facing privacy regulations (HIPAA, GDPR, PDPA, CCPA). Request a demo to learn more. Privacy Regulations are expanding beyond the current framework of IT infrastructure. Adapting to such a change is costly, time-consuming, and requires legal and development expertise. There is a better, more structured approach to data governance that responds and adapts to your complex IT environment, whether it’s on-cloud or on-premise. Take control of your compliance workflow and shape it according to business logic. Learn more about the solution trusted by large financial institutions across the globe.
