• Key Features ( Quick OVERVIEW )
• DBMS General Platform Features
• Data Storage and Update Features
• Database Search Features
• Database Indexing Features
• Centralized Management Features
• Security and User Administration
• Documentation and Code Samples
• Cross-platform Availability
• Hardware Requirements

Key Features ( Quick OVERVIEW )

• Native data storage clustering that scales out horizontally in cluster (cloud) architecture: our database platform is engineered for use in private, hybrid or public  'clouds', enabling to effortlessly scale out big data across multiple cluster servers. Please see Clustering;
  
  
• Customizable index ranking for the best search relevance and linear database scalability: being probably the most disruptive feature of our database software technology, it enables our customers to uniquely rank all content in their databases for custom relevance rules at database configuration level;  this search customization functionality is delivered by Clusterpoint Server for any database out-of-the-box, so that any database search query always returns results precisely positioned, grouped and ordered by those customer rankings, in the most useful and meaningful (relevant) way for end-users. Please see Information Ranking;
  
  
• Simplicity of database search: our customers can start using user-friendly, fast, precisely relevant database ad hoc search (including full text search) queries Internet-style in their database applications, so that there is no need to program software for strict query forms; users can use even free-format text terms to search their Clusterpoint databases and get expected relevant results; with this probably the most simplistic search format for end-users, they can still nearly instantly bring the most relevant database search results upfront, organized by database owner configured data ranking and relevancy rules using our programmable Information Ranking mechanism.  Please see Search;
  
  
• A hybrid key-based data store and document-store: undivided XML / JSON data objects stored by unique id key, a machine-readable database model easily understandable also by humans; for data storage and basic retrieval it works as a simple key-value data store, however for search it works as a structured data store enabling to perform combined structured, semi-structured and unstructured search queries that uses customer own data structure to select, narrow down or expand set of data objects retrieved based on customer own criteria (much like any SQL SELECT clause does).  Please see Technology;
  
  
• Scalable full text search index as integrated functionality: speed up data base full text search by orders of magnitude compared to most SQL and NoSQL solutions; simple,  free-format Internet-style search performance for web applications can be speed up to 1000 x with disk based database and up to 100 000x with in RAM memory based database. Please see Indexing;
  
  
• Sub-second query response times: Query with guaranteed response-times in range of 0.005 - 0.5 seconds (depending on RAM or disk storage).  Clusterpoint scales out to very large databases in clusters without performance loss, guaranteeing sub-second query response times in massively distributed databases with billions of XML / JSON data objects. Please see Performance;
  
  
• Rich enterprise search functionality: no need to integrate with enterprise search tools or platform, rich and powerful enterprise search functionality for unstructured data or for any textual data within structured data items is available out-of-the-box, including:
  
  • free format text search 
  • multiple words exact phrase search
  • word and phrase wildcards
  • letters matching wildcards for string pattern fast lookup
  • relevance scoring
  • customizable delimiter characters for custom text parsing
  • results snippets
  • hits high-lighting
  • custom vocabulary based search query expansion with synonyms or alternative word forms
  • index driven autocomplete using accumulated actual database content
  • word stemming by customizable syntax rules for a particular language
  • search by proximity of query terms
  • search by geo-location distance
  • return of query matching multi-level facets with hit counts (ideal for taxonomy, theme, product etc. dynamically built catalog- or menu- driven database navigation to narrow down or expand result set by one-click drill-down)
  • search for similar textual content
  • support for "Did you mean that?" spell-checking functionality using actual database content
  • forced inclusion or exclusion of search terms
  
  and many other advanced enterprise search options.  Please read more about it in Key Benefits and Search Simplicity;
  
  
• Transparent clustering hidden from customer software: Avoid complexity of distributed key value stores with key-sharding required for clustering; there is no need to program for clustering logic and key sharding in customer application software in Clusterpoint architecture; optionally our customers can still address particular cluster nodes to do application level data sharding if required, by specifying API parameters to work only on the local node, instead of default cluster-wide automatic clustering support in our API;
  
  
• Open API: based on open industry standard XML/JSON data format messaging and open industry standard web protocols (HTTP, HTTPS, REST, TCP/IP), very simple to learn and easy to use, with small, nearly self-explaining API command set.  Please see Clusterpoint API;
  
  
• Customizable server functionality: through server-side scripts written in free software LUA language. Customers can write and compile LUA scripts for their own custom functionality, which will be executed on the server before or after specified Clusterpoint API commands. These scripts are stored and executed on server side, providing speed, versatility and flexible extendability for a Clusterpoint Server software platform, implemented by customers themselves;  this mechanism also enables our customers to implement functionality which usually is provided only by stored procedures and triggers programmed in a vendor specific proprietary database platform language. Please see User Scripting;
  
  
• Elasticity: any Clusterpoint database can be effortlessly scaled out from a single server to massively clustered system distributed among hundreds of servers (cluster nodes). Please see Management;
  
  
• Cross-platform interoperability: we use only industry standard open data formats: robust and well supported by most software systems XML or more recent, developers' friendly JSON data format at Clusterpoint API level, maintaining industry standard XML data store format for internal Clusterpoint storage, so that our customers can choose either of the two best open data formats for their application software, and start building long-term vendor independent databases and software systems standardizing only on open data formats; this feature is crucial for interoperability between applications in multi-tier data center model, and, in particular, automated machine-to-machine web services;
  
  
• Allows completely de normalized database model maintaining high-performance:   store and manage human readable text values only, avoiding or eliminating complex relational encoding; de-normalization of database content works without any performance loss in Clusterpoint architecture;
  
  
• Customer data structure agnostic database:  any XML or JSON data objects with arbitrary data structure can be stored, managed and searched for in any Clusterpoint database through Clusterpoint API; a Clusterpoint database is "appearing" for application software as a simple key-based data store without particular restrictions of data object content (unless its values are stored as XML or JSON or as pure UTF-8 text); however internally all data is stored by Clusterpoint Server in industry standard XML and can be accessed in structured way, making Clusterpoint database to work at database access and search functionality more like a traditional SQL database or like a document store with precise structured data access whenever necessary; this double nature of Clusterpoint database makes it difficult sometimes to categorize it under one or another storage type;
  
  
• Fully indexed database content: instantly searchable database with "atomic" Indexing model, indexing all data items to the smallest elements (words, strings, tags, links, dates, numbers etc.);
  
  
• Client-server architecture: ideally fits model of multi-tier server environment, typical in corporate data centers with multiple load balanced web, application and database servers;
  
  
• High-performance software code: server software developed entirely in C/C++, optimized for modern multi-processor, multi-threading CPU computing architectures;
  
  
• Distributed cluster database: multi-master, no single point of failure cluster software architecture with real-time updates synchronization and integrity controls within a cluster;
  
  
• Automatic database replication in multiple copies: run full active database in multiple copies easily mirroring entire database into working identical copies located in different clusters or different data center locations;
  
  
• Real-time updates: all updates are performed in real-time, including full-text index updates, and available for search immediately afterwards;
  
  
• Atomic writes for reliability: f ollows ACID transaction model, making all database writes (updated) atomic with programmable check for either success or failure; Clusterpoint database model is designed for this atomicity of transactions;
  
  
• Parallel indexing/search: with Clusterpoint Server core engine designed for multi-core CPUs and priority based multi-threading, enables database real-time updates while search workload is serviced;
  
  
• Database virtualization by multiple instances of Clusterpoint server software: many Clusterpoint server instances per single hardware server can service different, safely partitioned customer databases, with their own secure user accounts, own access rights, own separate RAM address space use and disk storage use;
  
  
• Classic vendor-agnostic virtualization support:  same Clusterpoint database platform architecture also supports classic virtualization using virtual machines enabling to reuse hardware resources more efficiently in cloud IT infrastructure, so that our customers together with Database Virtualization by Multiple instances can safely run and flexibly scale cloud database services for different customers and different applications, each working with its own securely partitioned data storage and computing environment;
  
  
• Secure user authentication and access: Secure user authentication, with group and role based access rights for each storage, down to very detailed level of access rights to use individual API commands;
  
  
• Centralized enterprise-wide management with easy to use web-based GUI: create, configure, manage all servers, databases, clusters, perform full database mirroring, database backups, start and stop databases services, perform status check, view enterprise-wide dashboard of all Clusterpoint Servers, RAM, storage, log and audit files, all within a single GUI that can be accessible from anywhere using just a standard web browser, no special client software needed; supports one-click cluster-wide database configuration changes;
  
  
• Multiple administrator accounts, having different access rights: ideal for providing cloud database services for customers each having been restricted to their own database resources and functionality;
  
  
• Rich data management functionality for developers: more than 160 database indexing and search options available through Clusterpoint API and Clusterpoint Manager;
  
  
• Range and interval queries: numeric, dates, 2D, 3D or nD coordinates; using classic less than, more than, ascending, descending and other ordering methods that can be used in combination with full text search for unstructured data queries and with structured search queries, all three features within a single search query;
  
  
• Boolean AND, OR, NOT with multi-level unrestricted nesting of search query expressions: our API feature that enables our customers to program the most advanced, most complex and demanding business logic for precise data retrieval from combined structured and unstructured database content, that is normally required by business applications, previously using SQL programming for this type of complex search logic driven data retrieval; Clusterpoint Server achieves the same power of advanced data retrieval with much more simple to use, freely programmable mechanism that does not use SQL;
  
  
• Very large database (GB/TB/PB) storage capacity per database: data store can scale from hundreds of gigabytes per single hardware server to petabytes in massively clustered system, using inexpensive commodity hardware nodes with relatively modest computing and storage power; scaling this up with more powerful hardware as much as 64-bit hardware and underlying operating system and file system architecture allows; Clusterpoint Server software is written in C/C++ and can be easily ported to other OSes (currently we support packaged installations for Linux, FreeBSD and MacOS and a Virtual machine for Windows OS);
  
  
• File system agnostic storage: does not depend on particular file system unless it supports large file sizes per server;  if disk arrays are used, then theoretically it can support tens and hundreds of terabytes per server, however, for cost-efficiency and performance reasons it is recommended to distribute that big data size among cluster of commodity nodes; otherwise limited per server RAM amount and disk array through output together can create bottleneck, for example, starting to swap out portions of RAM, when databases size grows so big per single server, that hardware architecture starts negatively affect its performance;
  
  
• Automatic database index compression at high efficiency: a well-engineered compressed full content index for fast compression/decompression, that saves tons of storage space, taking into account that ranked full content index would normally require significant resources that can easily trump database storage size; it also saves storage I/O transactions and reduce the data size of individual I/O payload;
  
  
• Ease of integration with existing software platforms: no need for specialized client software if our web http/https/REST messaging is used; any popular programming language or development environment can start "talking" to Clusterpoint Server over those industry standard web services protocols using GET and POST, which makes any integration efforts a few-hours quick task;
  
  
• Optional client-side API libraries for native TCP protocol:  we also provide for developers Clusterpoint API libraries for the most popular programming languages (PHP, Java, .NET etc.) that uses direct TCP/IP client-server connection protocol for achieving the best transactional performance speeds over TCP network, if customer application requires every bit of performance for large workload, for large number of users or for large big data systems;  those programming language specific libraries are distributed under open source license, and we encourage developers to submit us their improved software versions and develop native TCP protocol based API libraries for other programming languages;
  
  
• Multi-lingual database storage: handles 160 languages in UTF-8 that is standard XML character encoding, where industry standard XML storage is used internally for Clusterpoint databases; supports automatic char set encoding conversion server-side for Clusterpoint API between UTF-8 and any other specific language encoding so that customer application software can be developed multi-lingual, and automatically performing required char set conversions (even if data was stored in a language specific encoding); this is very convenient for web applications, that need to access data form legacy databases that have very limited and restricted multi-language support.