AlternativeSoft
Since its inception in 2005, AlternativeSoft has revolutionized the way institutional investors select funds and construct portfolios. Our advanced alternative investment analytics platform empowers users to craft a tailored investment landscape supported by state-of-the-art analytics. The seamless integration of data from sources such as Bloomberg, Morningstar, Albourne, HFR, EurekaHedge, withintelligence, Preqin, and Refinitiv simplifies the process for users.
With our platform, users can efficiently:
- Assess manager risk/return through access to over 3,000 statistics on funds
- Establish a customizable investable universe using robust screening tools
- Monitor and evaluate fund exposures
- Build, optimize, and oversee portfolios
- Conduct thorough due diligence on hedge funds
- Generate reports on funds using PowerBI or Excel API
- Explore a vast array of options, including 500,000 mutual funds, 30,000 hedge funds, and 5,000 fundraising private equity funds, to determine the best choices available
With a combined total asset management of over $1.5 trillion globally, AlternativeSoft is trusted by some of the largest pension funds, fund of funds, family offices, private banks, endowments, foundations, wealth managers, and advisers to effectively identify and analyze diverse multi-asset class portfolios, encompassing hedge funds, mutual funds, and private equity funds. This trust underscores our commitment to providing cutting-edge solutions that cater to the complex needs of institutional investors.
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RaimaDB
RaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
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Warp 10
Warp 10 is an adaptable open-source platform designed for the collection, storage, and analysis of time series and sensor data. Tailored for the Internet of Things (IoT), it features a flexible data model that facilitates a seamless workflow from data gathering to analysis and visualization, while incorporating geolocated data at its core through a concept known as Geo Time Series. The platform provides both a robust time series database and an advanced analysis environment, enabling users to conduct various tasks such as statistical analysis, feature extraction for model training, data filtering and cleaning, as well as pattern and anomaly detection, synchronization, and even forecasting. Additionally, Warp 10 is designed with GDPR compliance and security in mind, utilizing cryptographic tokens for managing authentication and authorization. Its Analytics Engine integrates smoothly with numerous existing tools and ecosystems, including Spark, Kafka Streams, Hadoop, Jupyter, and Zeppelin, among others. Whether for small devices or expansive distributed clusters, Warp 10 accommodates a wide range of applications across diverse sectors, such as industry, transportation, health, monitoring, finance, and energy, making it a versatile solution for all your data needs. Ultimately, this platform empowers organizations to derive meaningful insights from their data, transforming raw information into actionable intelligence.
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kdb Insights
kdb Insights is a cloud-based advanced analytics platform designed for rapid, real-time evaluation of both current and historical data streams. It enables users to make well-informed decisions quickly, irrespective of data volume or speed, and offers a remarkable price-performance ratio, delivering analytics that is up to 100 times faster while costing only 10% compared to other alternatives. The platform features interactive visualizations through dynamic dashboards, which facilitate immediate insights that are essential for prompt decision-making. Furthermore, it utilizes machine learning models to enhance predictive capabilities, identify clusters, detect patterns, and assess structured data, ultimately boosting AI functionalities with time-series datasets. With its impressive scalability, kdb Insights can handle enormous volumes of real-time and historical data, efficiently managing loads of up to 110 terabytes each day. Its swift deployment and easy data ingestion processes significantly shorten the time required to gain value, while also supporting q, SQL, and Python natively, and providing compatibility with other programming languages via RESTful APIs. This flexibility allows users to seamlessly incorporate kdb Insights into their current workflows, maximizing its potential for various analytical tasks and enhancing overall operational efficiency. Additionally, the platform's robust architecture ensures that it can adapt to future data challenges, making it a sustainable choice for long-term analytics needs.
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