Alternatives to VictoriaMetrics

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RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times. RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.

VictoriaMetrics Cloud allows you to run VictoriaMetrics Enterprise on AWS without having to perform typical DevOps activities such as proper configuration and monitoring, log collection, security, software updates, software protection, or backups. We run VictoriaMetrics Cloud in our environment using AWS, and provide easy to use endpoints for data ingestion. VictoriaMetrics takes care of software maintenance and optimal configuration. It has the following features: It can be used to manage Prometheus. Configure Prometheus, Vmagent or VictoriaMetrics to write data into Managed VictoriaMetrics. Then use the endpoint provided as a Prometheus source in Grafana. Each VictoriaMetrics Cloud instance runs in a separate environment so that instances cannot interfere with one another; VictoriaMetrics Cloud can be scaled-up or scaled-down in just a few clicks. Automated backups.

QuestDB is an advanced relational database that focuses on column-oriented storage optimized for time series and event-driven data. It incorporates SQL with additional features tailored for time-based analytics to facilitate real-time data processing. This documentation encompasses essential aspects of QuestDB, including initial setup instructions, comprehensive usage manuals, and reference materials for syntax, APIs, and configuration settings. Furthermore, it elaborates on the underlying architecture of QuestDB, outlining its methods for storing and querying data, while also highlighting unique functionalities and advantages offered by the platform. A key feature is the designated timestamp, which empowers time-focused queries and efficient data partitioning. Additionally, the symbol type enhances the efficiency of managing and retrieving frequently used strings. The storage model explains how QuestDB organizes records and partitions within its tables, and the use of indexes can significantly accelerate read access for specific columns. Moreover, partitions provide substantial performance improvements for both calculations and queries. With its SQL extensions, users can achieve high-performance time series analysis using a streamlined syntax that simplifies complex operations. Overall, QuestDB stands out as a powerful tool for handling time-oriented data effectively.

VictoriaMetrics Enterprise, a commercial product designed by the creators VictoriaMetrics, is a solution for monitoring and observability in complex environments. It's perfect for organizations with large or rapidly scaling monitoring environments. The Enterprise edition includes all of the features in the Community Edition plus additional enhancements like Downsampling Automated backups / Backup manager Data Retention Per Label/Tenant Multi Tenant Statistic & Anomaly detection. It provides stable releases and long-term support to ensure critical bug fixes, security patches, and other enhancements. The package also includes enterprise security compliance and prioritised feature requests. We can help you reduce storage costs while improving performance of historical data queries. Multiple retentions allow different storage durations for various datasets. Automatic discovery of storage updates the list without restarting services at insert and vmselect.

VictoriaMetrics Anomaly Detection, a service which continuously scans data stored in VictoriaMetrics to detect unexpected changes in real-time, is a service for detecting anomalies in data patterns. It does this by using user-configurable models of machine learning. VictoriaMetrics Anomaly Detection is a key tool in the dynamic and complex world system monitoring. It is part of our Enterprise offering. It empowers SREs, DevOps and other teams by automating the complex task of identifying anomalous behavior in time series data. It goes beyond threshold-based alerting by utilizing machine learning to detect anomalies, minimize false positives and reduce alert fatigue. The use of unified anomaly scores and simplified alerting mechanisms allows teams to identify and address potential issues quicker, ensuring system reliability.

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/

VictoriaLogs is an open-source log-database from VictoriaMetrics that has been designed to be easy-to-use. It integrates seamlessly with popular log collectors, and offers a simpler setup process than Elasticsearch or Grafana Loki. LogsQL's robust query language allows for full-text searches across all log fields. This simplifies log management. It scales well with CPU, RAM and disk IO. It runs efficiently on Raspberry Pis and high-end servers. It can handle data volumes up 30 times greater than Elasticsearch or Grafana Loki, on the same hardware. This makes it a powerful option for various environments. VictoriaLogs supports full-text searches over log fields with high-cardinality like trace_id and IP. It integrates seamlessly with Unix log analysis programs like grep and less. It offers multi-tenancy, which can accommodate a variety of needs.

Blueflood is an advanced distributed metric processing system designed for high throughput and low latency, operating as a multi-tenant solution that supports Rackspace Metrics. It is actively utilized by both the Rackspace Monitoring team and the Rackspace public cloud team to effectively manage and store metrics produced by their infrastructure. Beyond its application within Rackspace, Blueflood also sees extensive use in large-scale deployments documented in community resources. The data collected through Blueflood is versatile, allowing users to create dashboards, generate reports, visualize data through graphs, or engage in any activities that involve analyzing time-series data. With a primary emphasis on near-real-time processing, data can be queried just milliseconds after it is ingested, ensuring timely access to information. Users send their metrics to the ingestion service and retrieve them from the Query service, while the system efficiently handles background rollups through offline batch processing, thus facilitating quick responses for queries covering extended time frames. This architecture not only enhances performance but also ensures that users can rely on rapid access to their critical metrics for effective decision-making.

KairosDB allows data ingestion through various protocols including Telnet, Rest, and Graphite, in addition to supporting plugins for further flexibility. It utilizes Cassandra, a well-regarded NoSQL database, to manage time series data effectively. The database schema is organized into three column families, facilitating efficient data storage. The API offers a range of functionalities, such as listing existing metric names, retrieving tag names and their corresponding values, storing metric data points, and querying these points for analysis. Upon a standard installation, users can access a query page that enables them to extract data from the database easily. This tool is primarily tailored for development applications. Aggregators within the system can perform operations on data points, allowing for down sampling and analysis. A set of standard functions, including min, max, sum, count, and mean, among others, are readily available for users to utilize. Additionally, the KairosDB server supports import and export functionalities via the command line interface. Internal metrics related to the database not only provide insights into the stored data but also allow for monitoring the performance of the server itself, ensuring optimal operation and efficiency. This comprehensive approach makes KairosDB a powerful solution for managing time series data.

BiblioTECH is a fully-featured Library Management System that was developed in Victoria, Australia. BiblioTECH was created in response to the needs of Librarians for an affordable Library Management System that is easy to use. The system's design was based on extensive market research, as well as input from active Librarians. BiblioTECH is a highly specialized and adaptable system that can be tailored to your library's needs. Modules Patrons Resources Circulation Search Reports

Hawkular Metrics is a robust, asynchronous, multi-tenant engine designed for long-term metrics storage, utilizing Cassandra for its data management and REST as its main interface. This segment highlights some of the essential characteristics of Hawkular Metrics, while subsequent sections will delve deeper into these features as well as additional functionalities. One of the standout aspects of Hawkular Metrics is its impressive scalability; its architecture allows for operation on a single instance with just one Cassandra node, or it can be expanded to encompass multiple nodes to accommodate growing demands. Moreover, the server is designed with a stateless architecture, facilitating easy scaling. Illustrated in the accompanying diagram are various deployment configurations enabled by the scalable design of Hawkular Metrics. The upper left corner depicts the most straightforward setup involving a lone Cassandra node connected to a single Hawkular Metrics node, while the lower right corner demonstrates a scenario where multiple Hawkular Metrics nodes can operate in conjunction with fewer Cassandra nodes, showcasing flexibility in deployment. Overall, this system is engineered to meet the evolving requirements of users efficiently.

Cortex is an innovative open-source solution that enhances horizontal scalability. While Prometheus is capable of handling up to 1 million samples per second on a single machine, Cortex enables a virtually limitless level of horizontal scaling. In an ever-evolving landscape, it is essential to adopt alternative strategies for monitoring individual virtual machines or servers. Prometheus features a service-discovery-driven, pull-based metrics system that caters to the dynamic characteristics of microservices. This capability allows for seamless monitoring of your entire ecosystem, regardless of the number of components involved. You can instrument your application to generate tailored metrics using the standard Prometheus client libraries, or you can leverage the vast array of Prometheus Exporters that gather data from existing software like MySQL, Redis, Java, ElasticSearch, and many others. By adopting these tools, organizations can ensure they maintain visibility and control over their complex infrastructures. This flexibility is particularly valuable in today's fast-paced, continuously changing technological environments.

Circonus IRONdb simplifies the management and storage of limitless telemetry data, effortlessly processing billions of metric streams. It empowers users to recognize both opportunities and challenges in real time, offering unmatched forensic, predictive, and automated analytics capabilities. With the help of machine learning, it automatically establishes a "new normal" as your operations and data evolve. Additionally, Circonus IRONdb seamlessly integrates with Grafana, which natively supports our analytics query language, and is also compatible with other visualization tools like Graphite-web. To ensure data security, Circonus IRONdb maintains multiple copies across a cluster of IRONdb nodes. While system administrators usually oversee clustering, they often dedicate considerable time to its upkeep and functionality. However, with Circonus IRONdb, operators can easily configure their clusters to run autonomously, allowing them to focus on more strategic tasks rather than the tedious management of their time series data storage. This streamlined approach not only enhances efficiency but also maximizes resource utilization.

Heroic is an open-source monitoring solution initially developed at Spotify to tackle challenges related to the large-scale collection and near real-time analysis of metrics. It comprises a limited number of specialized components that each serve distinct purposes. The system offers indefinite data retention, contingent upon adequate hardware investment, alongside federation capabilities that enable multiple Heroic clusters to connect and present a unified interface. A key component, Consumers, is tasked with the consumption of metrics, illustrating the system's design for efficiency. During the development of Heroic, it became evident that managing hundreds of millions of time series without sufficient context poses significant challenges. Additionally, the federation support facilitates the handling of requests across various independent Heroic clusters, allowing them to serve clients via a single global interface. This feature not only streamlines operations but also minimizes geographical traffic, as it allows individual clusters to function independently within their designated zones. Such capabilities ensure that Heroic remains a robust choice for organizations needing effective monitoring solutions.

A Time Series Database (TSDB) is designed for rapid data input and output, allowing for swift reading and writing of information. It achieves impressive compression rates that lead to economical data storage solutions. Moreover, this service facilitates visualization techniques, such as precision reduction, interpolation, and multi-metric aggregation, alongside the processing of query results. By utilizing TSDB, businesses can significantly lower their storage expenses while enhancing the speed of data writing, querying, and analysis. This capability allows for the management of vast quantities of data points and enables more frequent data collection. Its applications span various sectors, including IoT monitoring, enterprise energy management systems (EMSs), production security oversight, and power supply monitoring. Additionally, TSDB is instrumental in optimizing database structures and algorithms, capable of processing millions of data points in mere seconds. By employing an advanced compression method, it can minimize each data point's size to just 2 bytes, leading to over 90% savings in storage costs. Consequently, this efficiency not only benefits businesses financially but also streamlines operational workflows across different industries.

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.

For more than three decades, Fast Track has focused on offering risk-based quality and compliance management software tailored for medium to large enterprises. With a successful track record in notable organizations like Motorola, Serco, the Australian Department of Defence, and the Australian Quarantine Inspection Service, as well as in medical laboratories such as Alfred Hospital and Victoria Infectious Diseases Control Laboratories, you can trust Fast Track to ensure your regulatory compliance. As a recognized Microsoft Certified Partner, Fast Track delivers top-tier "On Premise" solutions, empowering you to maintain control over your data sovereignty, integrity, and security. Leveraging Microsoft’s .Net and SQL Server technologies, Fast Track provides support to clients not only across Australia but also globally, all from its headquarters situated in Queensland. This extensive experience and commitment to quality make Fast Track a standout choice in the compliance management sector.

Machbase is a leading time-series database designed for real-time storage and analysis of vast amounts of sensor data from various facilities. It stands out as the only database management system (DBMS) capable of processing and analyzing large datasets at remarkable speeds, showcasing its impressive capabilities. Experience the extraordinary processing speeds that Machbase offers! This innovative product allows for immediate handling, storage, and analysis of sensor information. It achieves rapid storage and querying of sensor data by integrating the DBMS directly into Edge devices. Additionally, it provides exceptional performance in data storage and extraction when operating on a single server. With the ability to configure multi-node clusters, Machbase offers enhanced availability and scalability. Furthermore, it serves as a comprehensive management solution for Edge computing, addressing device management, connectivity, and data handling needs effectively. In a fast-paced data-driven world, Machbase proves to be an essential tool for industries relying on real-time sensor data analysis.

Based in Miami, Florida, Gaumard Scientific specializes in developing advanced simulators for leading teaching hospitals, nursing schools, military medical training, and emergency medical services. Established in 1946, the company boasts more than 75 years of expertise in healthcare simulation, creating cutting-edge patient simulators, task trainers, educational modules, and mixed reality tools aimed at providing safe and effective training experiences for healthcare students and professionals across a wide range of clinical specialties. Their diverse product range features high-fidelity simulators, meticulously designed to offer realistic training scenarios in critical fields such as obstetrics, emergency care, pediatrics, and nursing. A prime example of their innovation is VICTORIA, a comprehensive birthing simulator that can accurately replicate a variety of childbirth events, from standard vaginal deliveries to C-sections, while also incorporating potential complications, thus allowing healthcare professionals to refine their skills in managing complex medical situations. This commitment to enhancing training through realistic simulations ensures that healthcare providers are well-prepared for the challenges they may face in real-world scenarios.

Minimize safety incidents by employing machine learning to identify and forecast patterns and irregularities, while also gaining insights into the root causes of accidents to mitigate future risks. Evaluate the effectiveness of safety initiatives, ensuring that performance is monitored and resources are allocated to the most impactful programs within your safety budget. Enhance adherence to regulatory requirements to prevent the financial and reputational repercussions of non-compliance. Effortlessly report hazardous conditions, malfunctioning equipment, near-misses, and injuries through user-friendly safety forms, and receive immediate alerts via email and SMS regarding safety events and risk situations in real time. Efficiently track and manage safety occurrences, leveraging our Robo-Analyst Victoria for predictive insights based on collected data. Gain valuable insights from your information, reduce paperwork and data entry efforts, and optimize time management for your business operations. By streamlining processes, you can save money and enhance the quality of your facility's safety data, ultimately fostering a safer working environment. Furthermore, continuous monitoring and improvement of safety measures will contribute to a culture of safety within the organization.

GreenAnt is dedicated to offering privacy-conscious services to both Australian and international clients. Our digital solutions are securely hosted in Australia, and we ensure that no data or metadata is shared with external parties. Additionally, GreenAntNetworks takes proactive steps to neutralize carbon emissions through sustainable tree-planting initiatives in Victoria, Australia. As an Australian web service and consulting provider with a rich history spanning twenty-five years, our expertise lies in data security and privacy. We cater to a diverse clientele that includes everything from small non-profits to major institutions. While some of these clients have simple data hosting requirements, others necessitate the creation of tailored software for intricate data management. We take immense pride in serving all of our clients, regardless of their size. A significant area of focus for us is providing specialized hosting and software solutions for healthcare professionals and researchers, illustrating our commitment to supporting critical sectors. By prioritizing both privacy and sustainability, we aim to make a positive impact in the digital landscape.

InfluxDB is a purpose-built data platform designed to handle all time series data, from users, sensors, applications and infrastructure — seamlessly collecting, storing, visualizing, and turning insight into action. With a library of more than 250 open source Telegraf plugins, importing and monitoring data from any system is easy. InfluxDB empowers developers to build transformative IoT, monitoring and analytics services and applications. InfluxDB’s flexible architecture fits any implementation — whether in the cloud, at the edge or on-premises — and its versatility, accessibility and supporting tools (client libraries, APIs, etc.) make it easy for developers at any level to quickly build applications and services with time series data. Optimized for developer efficiency and productivity, the InfluxDB platform gives builders time to focus on the features and functionalities that give their internal projects value and their applications a competitive edge. To get started, InfluxData offers free training through InfluxDB University.

TimescaleDB brings the power of PostgreSQL to time-series and event data at any scale. It extends standard Postgres with features like automatic time-based partitioning (hypertables), incremental materialized views, and native time-series functions, making it the most efficient way to handle analytical workloads. Designed for use cases like IoT, DevOps monitoring, crypto markets, and real-time analytics, it ingests millions of rows per second while maintaining sub-second query speeds. Developers can run complex time-based queries, joins, and aggregations using familiar SQL syntax — no new language or database model required. Built-in compression ensures long-term data retention without high storage costs, and automated data management handles rollups and retention policies effortlessly. Its hybrid storage architecture merges row-based performance for live data with columnar efficiency for historical queries. Open-source and 100% PostgreSQL compatible, TimescaleDB integrates with Kafka, S3, and the entire Postgres ecosystem. Trusted by global enterprises, it delivers the performance of a purpose-built time-series system without sacrificing Postgres reliability or flexibility.

CloudGuide serves as an ideal resource for enthusiasts of travel and culture who are eager to uncover new perspectives and experiences around the globe. With access to over 1,000 institutions spanning 26 countries, this app acts as a comprehensive guide to some of the most remarkable locations, including the Eiffel Tower in France, Spain's Sagrada Familia, the ancient Stonehenge in the UK, the Victoria and Albert Museum also in the UK, Austria's Vienna State Opera, the Museum of Science in the USA, and Belgium's Atomium, among countless others. You can explore a wide array of museums, historic landmarks, parks, and monuments nearby, allowing you to check their operational hours, learn about upcoming events, or even purchase tickets directly through the app. Furthermore, you can enhance your experience with multimedia-guided tours or transform your visit into an engaging treasure hunt, utilizing the interactive games and tours available within the application. With CloudGuide, every journey becomes an adventure filled with discovery and fun.

Utilibill offers Enterprise grade Utility Billing and CIS – Cloud native. We offer toolkits to utilities that allow them to transition independently. Additionally, we have a strong partner network that can help with the entire project lifecycle. We bill electricity, gas, water, re-water, air conditioning, broadband and many other services. Market connectivity includes: AEMO, NEMO and Telstra Wholesale, AAPT. Vocus, OPTUS, and many more. Our over 60-strong team is located in Victoria, California and Santa Monica, Arkansas. Provide: Billing CIS, Customer Portal and Invoice Designer. You can access our platforms for a 30-day free trial. Get yours today.

DeskCamera is innovative screen recording software designed specifically for video surveillance purposes. This tool transforms a Windows computer into a virtual IP camera, enabling the direct recording of desktop screens, application windows, webcams, and audio into any Video Management System (VMS) or Network Video Recorder (NVR), functioning just like traditional security cameras within the system. With no additional hardware required, DeskCamera serves as a software-only solution that can be installed within moments, replacing the need for video encoders, signal splitters, and cameras aimed at monitors. It is commonly utilized for various applications, including point-of-sale screen recording to combat retail theft, monitoring workstation activity in casinos, capturing SCADA and HMI screens, reviewing control-room operations, overseeing bank teller activities, recording airport displays, and converting RTSP streams to ONVIF. Key features include support for 4K resolution, frame rates of up to 60 FPS, GPU encoding through Intel QSV, NVIDIA NVENC, and AMD VCE technologies, multi-monitor streaming capabilities, picture-in-picture functionality, and motion detection events. DeskCamera partners with notable companies such as Milestone, Genetec, Pelco, Network Optix, and Digital Watchdog, among others, and is relied upon by esteemed organizations including Victoria Gate Casino, Universal Studios Japan, Siemens Energy, and Honeywell, showcasing its widespread trust and effectiveness in the industry. This versatility makes DeskCamera an essential tool for a wide range of surveillance needs.

The ITTIA DB suite brings together advanced features for time series, real-time data streaming, and analytics tailored for embedded systems, ultimately streamlining development processes while minimizing expenses. With ITTIA DB IoT, users can access a compact embedded database designed for real-time operations on resource-limited 32-bit microcontrollers (MCUs), while ITTIA DB SQL serves as a robust time-series embedded database that operates efficiently on both single and multicore microprocessors (MPUs). These ITTIA DB offerings empower devices to effectively monitor, process, and retain real-time data. Additionally, the products are specifically engineered to meet the needs of Electronic Control Units (ECUs) within the automotive sector. To ensure data security, ITTIA DB incorporates comprehensive protection mechanisms against unauthorized access, leveraging encryption, authentication, and the DB SEAL feature. Furthermore, ITTIA SDL adheres to the standards set forth by IEC/ISO 62443, reinforcing its commitment to safety. By integrating ITTIA DB, developers can seamlessly collect, process, and enhance incoming real-time data streams through a specialized SDK designed for edge devices, allowing for efficient searching, filtering, joining, and aggregating of data right at the edge. This comprehensive approach not only optimizes performance but also supports the growing demand for real-time data handling in today's technology landscape.

OpenTSDB comprises a Time Series Daemon (TSD) along with a suite of command line tools. Users primarily engage with OpenTSDB by operating one or more independent TSDs, as there is no centralized master or shared state, allowing for the scalability to run multiple TSDs as necessary to meet varying loads. Each TSD utilizes HBase, an open-source database, or the hosted Google Bigtable service for the storage and retrieval of time-series data. The schema designed for the data is highly efficient, enabling rapid aggregations of similar time series while minimizing storage requirements. Users interact with the TSD without needing direct access to the underlying storage system. Communication with the TSD can be accomplished through a straightforward telnet-style protocol, an HTTP API, or a user-friendly built-in graphical interface. To begin utilizing OpenTSDB, the initial task is to send time series data to the TSDs, and there are various tools available to facilitate the import of data from different sources into OpenTSDB. Overall, OpenTSDB's design emphasizes flexibility and efficiency for time series data management.

When PostgreSQL serves as the foundation of your enterprise and is a key data source, PeerDB offers an efficient, straightforward, and economical solution for replicating data from PostgreSQL to data warehouses, queues, and storage systems. It is engineered to function seamlessly at any scale and is specifically adapted for various data repositories. By utilizing replication messages sourced from the PostgreSQL replication slot, PeerDB adeptly replays schema updates while providing alerts for slot growth and active connections. It also includes native support for PostgreSQL toast columns and large JSONB columns, making it particularly advantageous for IoT applications. The platform features an optimized query architecture aimed at minimizing warehouse expenditures, which is especially beneficial for users of Snowflake and BigQuery. Additionally, it accommodates partitioned tables through both publication mechanisms. PeerDB ensures rapid and reliable initial data loads via transaction snapshotting and CTID scanning techniques. With features such as high availability, in-place upgrades, autoscaling, advanced logging, comprehensive metrics, and monitoring dashboards, as well as burstable instance types, it is also well-suited for development environments. Overall, PeerDB stands out as a versatile tool that effectively meets the diverse needs of modern data management.

Plus500 stands out as a prominent provider of Contracts for Difference (CFDs), offering trading opportunities across a diverse range of assets including shares, forex, commodities, cryptocurrencies, ETFs, options, and indices, all powered by cutting-edge trading technology. The trading platform is operated by Plus500SEY Ltd, which is responsible for issuing and selling the financial products featured on its website. Located in Victoria, Seychelles, Plus500SEY Ltd is regulated by the Seychelles Financial Services Authority (FSA) under license number SD039, enabling it to provide Contracts for Difference (CFDs) on various underlying assets. As a rapidly expanding CFD provider, the company boasts a portfolio that exceeds 2,000 instruments. Furthermore, Plus500SEY Ltd operates as a subsidiary of Plus500 Ltd, a publicly traded company on the London Stock Exchange’s Main Market for Listed Companies, with its headquarters situated in Haifa. In addition to its robust regulatory framework, Plus500 continues to enhance its offerings to cater to the evolving needs of its traders.

Related Marketing Cloud (RMC), a personalization and marketing automation tool for data-driven Omnichannel marketing, is available. One-to-one customer relationships powered by all-in-one platform to drive higher revenues, increase customer lifetime value, grow audience, boost performance, and drive higher revenue. We are proud that we offer the following services: Customer Data Platform (Email Marketing, Mobile Marketing), Web Targeting, Product Recommendation and Customer Journey Manager

Warp 10 is a modular open source platform that collects, stores, and allows you to analyze time series and sensor data. Shaped for the IoT with a flexible data model, Warp 10 provides a unique and powerful framework to simplify your processes from data collection to analysis and visualization, with the support of geolocated data in its core model (called Geo Time Series). Warp 10 offers both a time series database and a powerful analysis environment, which can be used together or independently. It will allow you to make: statistics, extraction of characteristics for training models, filtering and cleaning of data, detection of patterns and anomalies, synchronization or even forecasts. The Platform is GDPR compliant and secure by design using cryptographic tokens to manage authentication and authorization. The Analytics Engine can be implemented within a large number of existing tools and ecosystems such as Spark, Kafka Streams, Hadoop, Jupyter, Zeppelin and many more. From small devices to distributed clusters, Warp 10 fits your needs at any scale, and can be used in many verticals: industry, transportation, health, monitoring, finance, energy, etc.

KPC Business Centre stands out as a premier provider of business services in Hong Kong, offering a range of solutions including serviced offices with stunning harbour views, virtual office arrangements, meeting spaces, company formation assistance, and visa application support. Located at the bustling heart of Tsim Sha Tsui, a district famous for its commercial vibrancy and entertainment options, our Centre benefits from proximity to numerous world-class hotels and a well-connected public transportation network, ensuring swift access to every corner of the city. Our strategic location next to the East Tsim Sha Tsui MTR Station and near the prestigious Kowloon Shangri-La Hotel positions us perfectly for both convenience and accessibility. With luxury accommodations and cultural landmarks nearby, clients can enjoy impressive panoramic views of Victoria Harbour and the iconic skyline of Hong Kong Island while conducting their business. This makes KPC Business Centre an ideal choice to cater to all your professional requirements. Whether you are seeking a temporary workspace or looking to establish a permanent presence, our Centre is equipped to fulfill your business aspirations with excellence.

Azure Time Series Insights Gen2 is a robust and scalable IoT analytics service that provides an exceptional user experience along with comprehensive APIs for seamless integration into your current workflow or application. This platform enables the collection, processing, storage, querying, and visualization of data at an Internet of Things (IoT) scale, ensuring that the data is highly contextualized and specifically tailored for time series analysis. With a focus on ad hoc data exploration and operational analysis, it empowers users to identify hidden trends, detect anomalies, and perform root-cause investigations. Furthermore, Azure Time Series Insights Gen2 stands out as an open and adaptable solution that caters to the diverse needs of industrial IoT deployments, making it an invaluable tool for organizations looking to harness the power of their data. By leveraging its capabilities, businesses can gain deeper insights into their operations and make informed decisions to drive efficiency and innovation.

The enterprise database for time series, documents, and vectors. Store any type data and combine the simplicity and scalability NoSQL with SQL. CrateDB is a distributed database that runs queries in milliseconds regardless of the complexity, volume, and velocity.

JaguarDB facilitates the rapid ingestion of time series data while integrating location-based information. It possesses the capability to index data across both spatial and temporal dimensions effectively. Additionally, the system allows for swift back-filling of time series data, enabling the insertion of significant volumes of historical data points. Typically, time series refers to a collection of data points that are arranged in chronological order. However, in JaguarDB, time series encompasses both a sequence of data points and multiple tick tables that hold aggregated data values across designated time intervals. For instance, a time series table in JaguarDB may consist of a primary table that organizes data points in time sequence, along with tick tables that represent various time frames such as 5 minutes, 15 minutes, hourly, daily, weekly, and monthly, which store aggregated data for those intervals. The structure for RETENTION mirrors that of the TICK format but allows for a flexible number of retention periods, defining the duration for which data points in the base table are maintained. This approach ensures that users can efficiently manage and analyze historical data according to their specific needs.

Established in 2000, Daz 3D is a company that focuses on 3D modeling software and content, particularly known for its versatile, posable human models, including the globally popular figures Victoria and Michael. Catering to both novices and experienced graphic artists, Daz Studio offers a free and efficient platform for creating and personalizing a wide range of artistic projects. The software finds applications in various industries such as film, television, animation, video gaming, web design, and print illustration. Users can download Daz Studio to access an extensive collection of both complimentary and premium 3D assets, enabling them to design unique scenes and characters in mere moments. With the intuitive smart content library, artists can quickly piece together their imaginative concepts. Daz Studio empowers creators to produce stunning, photo-realistic visuals and animations using advanced studio-class processing techniques. Moreover, the platform allows users to craft their own expansive universes filled with diverse characters, environments, and vehicles, making it a versatile tool for any creative endeavor. Dive into the world of 3D creation with Daz Studio and unlock endless possibilities for your artistic expressions.

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.

Amazon Timestream is an efficient, scalable, and serverless time series database designed for IoT and operational applications, capable of storing and analyzing trillions of events daily with speeds up to 1,000 times faster and costs as low as 1/10th that of traditional relational databases. By efficiently managing the lifecycle of time series data, Amazon Timestream reduces both time and expenses by keeping current data in memory while systematically transferring historical data to a more cost-effective storage tier based on user-defined policies. Its specialized query engine allows users to seamlessly access and analyze both recent and historical data without the need to specify whether the data is in memory or in the cost-optimized tier. Additionally, Amazon Timestream features integrated time series analytics functions, enabling users to detect trends and patterns in their data almost in real-time, making it an invaluable tool for data-driven decision-making. Furthermore, this service is designed to scale effortlessly with your data needs while ensuring optimal performance and cost efficiency.

KX Streaming Analytics offers a comprehensive solution for ingesting, storing, processing, and analyzing both historical and time series data, ensuring that analytics, insights, and visualizations are readily accessible. To facilitate rapid productivity for your applications and users, the platform encompasses the complete range of data services, which includes query processing, tiering, migration, archiving, data protection, and scalability. Our sophisticated analytics and visualization tools, which are extensively utilized in sectors such as finance and industry, empower you to define and execute queries, calculations, aggregations, as well as machine learning and artificial intelligence on any type of streaming and historical data. This platform can be deployed across various hardware environments, with the capability to source data from real-time business events and high-volume inputs such as sensors, clickstreams, radio-frequency identification, GPS systems, social media platforms, and mobile devices. Moreover, the versatility of KX Streaming Analytics ensures that organizations can adapt to evolving data needs and leverage real-time insights for informed decision-making.

Proficy Historian stands out as a premier historian software solution designed to gather industrial time-series and A&E data at remarkable speeds, ensuring secure and efficient storage, distribution, and rapid access for analysis, ultimately enhancing business value. With a wealth of experience and a track record of thousands of successful implementations globally, Proficy Historian transforms how organizations operate and compete by making critical data accessible for analyzing asset and process performance. The latest version of Proficy Historian offers improved usability, configurability, and maintainability thanks to significant advancements in its architecture. Users can leverage the solution's powerful yet straightforward features to derive new insights from their equipment, process data, and business strategies. Additionally, the remote collector management feature enhances user experience, while horizontal scalability facilitates comprehensive data visibility across the enterprise, making it an essential tool for modern businesses. By adopting Proficy Historian, companies can unlock untapped potential and drive operational excellence.

kdb Insights is an advanced analytics platform built for the cloud, enabling high-speed real-time analysis of both live and past data streams. It empowers users to make informed decisions efficiently, regardless of the scale or speed of the data, and boasts exceptional price-performance ratios, achieving analytics performance that is up to 100 times quicker while costing only 10% compared to alternative solutions. The platform provides interactive data visualization through dynamic dashboards, allowing for immediate insights that drive timely decision-making. Additionally, it incorporates machine learning models to enhance predictive capabilities, identify clusters, detect patterns, and evaluate structured data, thereby improving AI functionalities on time-series datasets. With remarkable scalability, kdb Insights can manage vast amounts of real-time and historical data, demonstrating effectiveness with loads of up to 110 terabytes daily. Its rapid deployment and straightforward data ingestion process significantly reduce the time needed to realize value, while it natively supports q, SQL, and Python, along with compatibility for other programming languages through RESTful APIs. This versatility ensures that users can seamlessly integrate kdb Insights into their existing workflows and leverage its full potential for a wide range of analytical tasks.

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.

Tiger Data reimagines PostgreSQL for the modern era — powering everything from IoT and fintech to AI and Web3. As the creator of TimescaleDB, it brings native time-series, event, and analytical capabilities to the world’s most trusted database engine. Through Tiger Cloud, developers gain access to a fully managed, elastic infrastructure with auto-scaling, high availability, and point-in-time recovery. The platform introduces core innovations like Forks (copy-on-write storage branches for CI/CD and testing), Memory (durable agent context and recall), and Search (hybrid BM25 and vector retrieval). Combined with hypertables, continuous aggregates, and materialized views, Tiger delivers the speed of specialized analytical systems without sacrificing SQL simplicity. Teams use Tiger Data to unify real-time and historical analytics, build AI-driven workflows, and streamline data management at scale. It integrates seamlessly with the entire PostgreSQL ecosystem, supporting APIs, CLIs, and modern development frameworks. With over 20,000 GitHub stars and a thriving developer community, Tiger Data stands as the evolution of PostgreSQL for the intelligent data age.