Best Data Management Software in the UK - Page 95
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Compare the Top Data Management Software in the UK as of June 2026 - Page 95
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Apache Anakia
The Apache Software Foundation
Anakia is potentially easier to learn than XSL, but it maintains a similar level of functionality. Learning cryptic <xsl:> tags is unnecessary; you only need to know how to use the provided Context objects, JDOM, and Velocity's simple directives. Anakia seems to perform much faster than Xalan's XSL processor at creating pages. (23 pages are generated in 7-8 seconds on a PIII 500mhz running Win98 and JDK 1.3 with client Hotspot. A similar system using Ant's <style> task took 14-15 seconds -- nearly a 2x speed improvement.) Anakia -- intended to replace Stylebook, which was originally used to generate simple, static web sites in which all pages had the same look and feel -- is great for documentation/project web sites, such as the sites on www.apache.org and jakarta.apache.org. As it is more targeted to a specific purpose, it does not provide some of XSL's "extra" functionality. -
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Apache Santuario
The Apache Software Foundation
Apache XML Security for Java: This library includes the standard JSR-105 (Java XML Digital Signature) API, a mature DOM-based implementation of both XML Signature and XML Encryption, as well as a more recent StAX-based (streaming) XML Signature and XML Encryption implementation. Ability to set a security provider when using org.apache.xml.security.signature.XMLSignature. Added support for customizing how to parse a Inputstream into a DOM Document. -
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Apache Xalan
The Apache Software Foundation
The Apache Xalan Project develops and maintains libraries and programs that transform XML documents using XSLT standard stylesheets. Our subprojects use the Java and C++ programing languages to implement the XSLT libraries. The Xalan-Java 2.7.2 was released in April 2014. You can download the current release the current Xalan-Java 2.7.2 release for your development. The current work in progress can be found in the subversion repository. The current release fixes a security issue that was registered against version 2.7.1. The old Xalan-J 2.7.1 distributions are still available on the Apache Archives. This is a mature project. There has been some discussion about supporting XPath-2. We could use your support in this major rework of the library. You can follow the efforts and post your own contributions on the Java users and developers mail lists. -
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Apache Axiom
The Apache Software Foundation
The Apache Axiom™ library provides an XML Infoset compliant object model implementation which supports on-demand building of the object tree. It supports a novel "pull-through" model which allows one to turn off the tree building and directly access the underlying pull event stream using the StAX API. It also has built in support for XML Optimized Packaging (XOP) and MTOM, the combination of which allows XML to carry binary data efficiently and in a transparent manner. The combination of these is an easy to use API with a very high performant architecture! Developed as part of Apache Axis2, Apache Axiom is the core of Apache Axis2. However, it is a pure standalone XML Infoset model with novel features and can be used independently of Apache Axis2. -
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StoredIQ
Breakwater
StoredIQ for information governance, for legal, for policy management, and StoredIQ InstaScan. StoredIQ provides a holistic solution for addressing data management challenges relating to compliance, e-discovery, records management, storage optimization, and data migration. Robust electronic discovery (eDiscovery) process management from hold notification to identification, preservation, and collection. Intelligent file analysis tool that leverages automation and statistical sampling models to identify risk hot spots in unstructured cloud data. Helps eliminate information management risks by offering centralized retention controls to support your business and legal requirements. By providing an in-depth assessment of unstructured data across the enterprise and where it resides, Breakwater can help your organization implement business-ready data and drive your organization’s digital transformation. -
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Brainwave GRC
Radiant Logic
Brainwave is reinventing the way you analyze your user accesses! You will now be able to thoroughly analyze access risk thanks to a new user interface, predictive controls and risk-scoring functionality. With Autonomous Identity, you can engage your teams and improve their efficiency with a market-approved, ergonomic tool that accelerates your identity management program (IGA). Enable the business to review and make decisions about access to shared files and folders. Inventory, classify, review access and demonstrate compliance regardless of the location, file servers, NAS, Sharepoint, Office 365 and others. Our core product, Brainwave Identity GRC, provides a wealth of analytical capabilities to leverage the inventory of all access. Obtain full visibility at all time, on all resources. Brainwave’s inventory constitutes an entitlement catalog across infrastructure, business applications and data access. -
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Solvuu
Solvuu
A data science platform for life scientists. Translate your microbiome research into practical applications. Bring novel, safe and effective products to market faster. Integrate the right set of data science and collaboration tools, and achieve rapid advances in cancer therapeutics. Accelerate research, enable innovation and create value by adopting effective digital technology solutions to improve crop productivity. Import your small and big data. Organize according to our templates, or define your own schema. Our format inference algorithm synthesizes parsing functions and lets you override if needed, without coding. Use our interactive import screens or CLI for bulk imports. Your data is not just bytes. Solvuu automatically computes relevant summary statistics and generates rich interactive visualizations. Explore and gain insights into your data immediately; slice and dice as needed. -
8
OpenHexa
Bluesquare
Understanding health issues often requires combining complex and heterogeneous data sources, even in the context of single-country interventions. Data can come from HMIS platforms such as DHIS2, from individual tracking systems, from custom software built to address specific issues, or from various Excel reports provided by health experts. Having such diverse data in disconnected silos is often the biggest obstacle to an efficient exploration and analysis process. It also makes collaboration difficult, and many data analysts working on health data end up developing ad-hoc scripts and visualisations on their own laptops and communicating their results in scattered publications from which it is hard to get unified insights. To address this issue, Bluesquare has built OpenHexa, a cloud-based data integration platform consisting of three components, extraction, analysis & visualization. This platform is mostly based on mature open-source technologies. -
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Apache Kylin
Apache Software Foundation
Apache Kylin™ is an open source, distributed Analytical Data Warehouse for Big Data; it was designed to provide OLAP (Online Analytical Processing) capability in the big data era. By renovating the multi-dimensional cube and precalculation technology on Hadoop and Spark, Kylin is able to achieve near constant query speed regardless of the ever-growing data volume. Reducing query latency from minutes to sub-second, Kylin brings online analytics back to big data. Kylin can analyze 10+ billions of rows in less than a second. No more waiting on reports for critical decisions. Kylin connects data on Hadoop to BI tools like Tableau, PowerBI/Excel, MSTR, QlikSense, Hue and SuperSet, making the BI on Hadoop faster than ever. As an Analytical Data Warehouse, Kylin offers ANSI SQL on Hadoop/Spark and supports most ANSI SQL query functions. Kylin can support thousands of interactive queries at the same time, thanks to the low resource consumption of each query. -
10
Q-Bot
bi3 Technologies
Qbot is an Automated test engine, purpose build for data quality. It enabling large, complex data platform but environment & ETL or Database technology agnostic. It can be used for ETL Testing, ETL platform upgrades, Database Upgrades, Cloud migration or Big Data migration Qbot deliver trusted quality data at the speed you never seen before. One of the most comprehensive Data quality automation engines built with: data security, scalability, speed and most extensive test library. Here the user can directly pass the SQL Query while configuring the test group. We currently support the below database servers for source and target database tables. -
11
SSAS
Microsoft
Installed as an on-premises server instance, SQL Server Analysis Services supports tabular models at all compatibility levels (depending on version), multidimensional models, data mining, and Power Pivot for SharePoint. A typical implementation workflow includes installing a SQL Server Analysis Services instance, creating a tabular or multidimensional data model, deploying the model as a database to a server instance, processing the database to load it with data, and then assigning permissions to allow data access. When ready to go, the data model can be accessed by any client application supporting Analysis Services as a data source. Models are populated with data from external data systems, usually data warehouses hosted on a SQL Server or Oracle relational database engine (Tabular models support additional data source types). -
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By managing data properly over its lifetime, organizations are better equipped to support business goals with less risk. Archive data from decommissioned applications and historical transaction records, while providing ongoing access to the data for query and reporting that is compliant with retention regulations. Scale data across applications, databases, operating systems and hardware platforms to help secure your test environments, accelerate release cycles and reduce costs. Lack of data archiving can impair the performance of mission-critical enterprise systems. Solve data growth problems at the source, improve efficiency and minimize the risks associated with managing structured data throughout its lifetime. Protect unstructured data in testing, development and analytics environments across the enterprise. Lack of data archiving can impair the performance of mission-critical enterprise systems. Solve data growth problems at the source, improve efficiency and minimize the risks.
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13
Zetaris
Zetaris
Rather than uploading the data to a central place to analyze it, Zetaris enables instant analytics across all your data, now. This means you can connect multiple databases and analyze them together in real-time, without the time and cost (and fail rate) associated with moving the data to a central location. Our unique analytical query optimizer ensures speed and scalability for whatever query is being run, across any combination of data sources. Ensure data governance and security by not moving data, and analyzing it at its source. Don't move the data. No data extraction, no data transformation, no copying of data to another repository. Remove unnecessary storage, processing and support costs, thanks to zero data duplication. -
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StreamScape
StreamScape
Make use of Reactive Programming on the back-end without the need for specialized languages or cumbersome frameworks. Triggers, Actors and Event Collections make it easy to build data pipelines and work with data streams using simple SQL-like syntax, shielding users from the complexities of distributed system development. Extensible Data Modeling is a key feature that supports rich semantics and schema definition for representing real-world things. On-the-fly validation and data shaping rules support a variey of formats like XML and JSON, allowing you to easily describe and evolve your schema, keeping pace with changing business requirements. If you can describe it, we can query it. Know SQL and Javascript? Then you already know how to use the data engine. Whatever the format, a powerful query language lets you instantly test logic expressions and functions, speeding up development and simplifying deployment for unmatched data agility. -
15
Teradata QueryGrid
Teradata
Deploying multiple analytic engines means best-fit engineering, so QueryGrid lets users leverage the right tool for the job. SQL is the language of business, and QueryGrid delivers unparalleled SQL access across commercial and open source analytical engines. Built for a hybrid multi-cloud reality, Vantage solves the world’s most complex data challenges at scale. Software that delivers autonomy, visibility, and insights to keep pace with changing customer demand. -
16
CluedIn
CluedIn
CluedIn has the quickest implementation time of any master data management platform on the market. CluedIn has transformed traditional MDM into an augmented experience. Less manual work. Better results. This is simply impossible with traditional MDM. CluedIn has revolutionized a new type of MDM with no restrictions. CluedIn has been designed to remove the standard complexities with traditional MDM. CluedIn is a cloud-native Master Data Management platform that was built to run at low cost. Enterprise software that has the onboarding simplicity of buying a SAAS platform. Whereas traditional MDM vendors will ask you to stitch together different products into an end to end story, we have stitched together the common pillars of master data management for you. We took a knife to traditional master data management and came out the other side with techniques that automate the hardest parts of the process and render traditional approaches as obsolete.Starting Price: $28,500 per year -
17
Fraxses
Intenda
There are many products on the market that can help companies to do this, but if your priorities are to create a data-driven enterprise and to be as efficient and cost-effective as possible, then there is only one solution you should consider: Fraxses, the world’s foremost distributed data platform. Fraxses provides customers with access to data on demand, delivering powerful insights via a solution that enables a data mesh or data fabric architecture. Think of a data mesh as a structure that can be laid over disparate data sources, connecting them, and enabling them to function as a single environment. Unlike other data integration and virtualization platforms, the Fraxses data platform has a decentralized architecture. While Fraxses fully supports traditional data integration processes, the future lies in a new approach, whereby data is served directly to users without the need for a centrally owned data lake or platform. -
18
Infinidat Elastic Data Fabric
Infinidat
The consumer datasphere’s huge growth over the past decade is now being overshadowed by exponential growth rates in business data. This presents unprecedented opportunities and challenges for enterprises and cloud service providers, requiring a fundamentally new approach to building and scaling storage infrastructure. Infinidat Elastic Data Fabric is our vision for the evolution of enterprise storage from traditional hardware appliances into elastic data center-scale pools of high-performance, highly reliable, low-cost digital storage with seamless data mobility within the data center and the public cloud. Today, enterprise technologists in every industry are facing a similar dilemma, thanks to the tsunami of digital transformation. Traditional hardware-based storage arrays are expensive, hard to manage, and orders of magnitude too small for the coming data age. They must, therefore, evolve into something new: softwaredefined on-premises enterprise storage clouds. -
19
Doc.Mobility
Doc.Series
Access your documents in comfort, anywhere and without wasting time, thanks to the Doc.Mobility solution. No matter where you are, you can easily find and view documents on screen. Doc.Mobility allows you to connect from a mobile device (tablet or smartphone) in order to access the electronic document management application to consult information, access your tasks and produce documents. This module allows you to work comfortably while roaming. All these functions are carried out in compliance with the security policies of the companies. The use of a protocol encrypting data during the connection between your electronic document management system and your tablet or smartphone ensures secure transmission of data and documents. With Doc.Mobility, you use all the user-friendly functions and ergonomics of the interface of your tablet or smartphone. You browse, select actions with your fingertips, you zoom with your thumb and forefinger as you are used to on your mobile devices. -
20
Oracle TimesTen
Oracle
Oracle TimesTen In-Memory Database (TimesTen) delivers real time application performance (low response time and high throughput) by changing the assumptions around where data resides at runtime. By managing data in memory, and optimizing data structures and access algorithms accordingly, database operations execute with maximum efficiency achieving dramatic gains in responsiveness and throughput. With the introduction of TimesTen Scaleout, a shared nothing scale-out architecture based on the existing in-memory technology, TimesTen allows databases to transparently scale across dozens of hosts, reach hundreds of terabytes in size and support hundreds of millions of transactions per second without the need for manual database sharding or workload partitioning. -
21
Apache Geode
Apache
Build high-speed, data-intensive applications that elastically meet performance requirements at any scale. Take advantage of Apache Geode's unique technology that blends advanced techniques for data replication, partitioning and distributed processing. Apache Geode provides a database-like consistency model, reliable transaction processing and a shared-nothing architecture to maintain very low latency performance with high concurrency processing. Data can easily be partitioned (sharded) or replicated between nodes allowing performance to scale as needed. Durability is ensured through redundant in-memory copies and disk-based persistence. Super fast write-ahead-logging (WAL) persistence with a shared-nothing architecture that is optimized for fast parallel recovery of nodes or an entire cluster. -
22
Ehcache
Terracotta
Ehcache is an open source, standards-based cache that boosts performance, offloads your database, and simplifies scalability. It's the most widely-used Java-based cache because it's robust, proven, full-featured, and integrates with other popular libraries and frameworks. Ehcache scales from in-process caching, all the way to mixed in-process/out-of-process deployments with terabyte-sized caches. Terracotta actively develops, maintains, and supports Ehcache as a professional open source project available under an Apache 2.0 license. Contributors are welcome to join our community. -
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Apache Superset
Apache
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. -
24
LevelDB
Google
LevelDB is a fast key-value storage library written at Google that provides an ordered mapping from string keys to string values. Keys and values are arbitrary byte arrays. Data is stored sorted by key. Callers can provide a custom comparison function to override the sort order. Multiple changes can be made in one atomic batch. Users can create a transient snapshot to get a consistent view of data. Forward and backward iteration is supported over the data. Data is automatically compressed using the Snappy compression library. External activity (file system operations etc.) is relayed through a virtual interface so users can customize the operating system interactions. We use a database with a million entries. Each entry has a 16 byte key, and a 100 byte value. Values used by the benchmark compress to about half their original size. We list the performance of reading sequentially in both the forward and reverse direction, and also the performance of a random lookup. -
25
Mnesia
Erlang
The management of data in telecommunications systems has many aspects of which some, but not all, are addressed by traditional Database Management Systems (DBMSs). In particular, the high level of fault tolerance required in many nonstop systems, combined with requirements on the DBMS to run in the same address space as the applications, have led us to implement a new DBMS, called Mnesia. Mnesia is implemented in, and tightly coupled to Erlang. It provides the functionality that is necessary for the implementation of fault-tolerant telecommunications systems. Mnesia is a multiuser distributed DBMS specifically designed for industrial-grade telecommunications applications written in Erlang, which is also the intended target language. Mnesia tries to address all the data management issues required for typical telecommunications systems and has a number of features not normally found in traditional DBMSs. -
26
upscaledb
upscaledb
upscaledb is a fast key-value database which optimizes storage and algorithms for your specific data types. Optional compression further reduces file size and I/O, and can keep more data in memory to increase performance and scalability when running full-table scans to query and analyze the data. upscaledb can be used to build all functions of a typical SQL database, tailored to the specific needs of your application, and directly linked into your program. Its blazingly fast analytical functions and database cursors make it a natural fit to process data whenever a SQL database is not fast enough. Applications using upscaledb are deployed on tens of millions of desktops, but also on cloud instances, cell phones and other embedded devices. This benchmark runs a full-table scan over 50 million records and retrieves the maximum. The records are configured as uint32 values. -
27
FoundationDB
FoundationDB
FoundationDB is multi-model, meaning you can store many types data in a single database. All data is safely stored, distributed, and replicated in the Key-Value Store component. FoundationDB is easy to install, grow, and manage. It has a distributed architecture that gracefully scales out, and handles faults while acting like a single ACID database. FoundationDB provides amazing performance on commodity hardware, allowing you to support very heavy loads at low cost. FoundationDB has been running in production for years and been hardened with lessons learned. Backing FoundationDB up is an unmatched testing system based on a deterministic simulation engine. We encourage your participation in our open-source community! Join us in technical and user discussions on the community forums, and learn how to contribute. -
28
Azure Table Storage
Microsoft
Use Azure Table storage to store petabytes of semi-structured data and keep costs down. Unlike many data stores—on-premises or cloud-based—Table storage lets you scale up without having to manually shard your dataset. Availability also isn’t a concern: using geo-redundant storage, stored data is replicated three times within a region—and an additional three times in another region, hundreds of miles away. Table storage is excellent for flexible datasets—web app user data, address books, device information, and other metadata—and lets you build cloud applications without locking down the data model to particular schemas. Because different rows in the same table can have a different structure—for example, order information in one row, and customer information in another—you can evolve your application and table schema without taking it offline. Table storage embraces a strong consistency model. -
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VMware Tanzu GemFire
Broadcom
VMware Tanzu GemFire is a distributed, in-memory, key-value store that performs read and write operations at blazingly fast speeds. It offers highly available parallel message queues, continuous availability, and an event-driven architecture you can scale dynamically, with no downtime. As your data size requirements increase to support high-performance, real-time apps, Tanzu GemFire can scale linearly with ease. Traditional databases are often too brittle or unreliable for use with microservices. That’s why every modern distributed architecture needs a cache! With Tanzu GemFire, applications get low-latency responses to data access requests, and always return fresh data. Your applications can subscribe to real-time events to react to changes immediately. Tanzu GemFire’s continuous queries notify your application when new data is available, which reduces the overhead on your SQL database. -
30
Apache Accumulo
Apache Corporation
With Apache Accumulo, users can store and manage large data sets across a cluster. Accumulo uses Apache Hadoop's HDFS to store its data and Apache ZooKeeper for consensus. While many users interact directly with Accumulo, several open source projects use Accumulo as their underlying store. To learn more about Accumulo, take the Accumulo tour, read the user manual and run the Accumulo example code. Feel free to contact us if you have any questions. Accumulo has a programming mechanism (called Iterators) that can modify key/value pairs at various points in the data management process. Every Accumulo key/value pair has its own security label which limits query results based off user authorizations. Accumulo runs on a cluster using one or more HDFS instances. Nodes can be added or removed as the amount of data stored in Accumulo changes.
