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index the platform columnar time series database home news contact playground pdf introduction platform general installation usage tutorial language reference overview types overview scalars overview guids symbols temporal types vectors strings dictionaries tables creation indexing meta information arithmetics modification inserts on disk partitioned tables signals reagents overview async bus deq file ipc kdb kdblistener listener log null state sync timer tcp tty tls udp ws attributes pattern matching lambdas shadow assign assign 0 assign 1 destructuring verbs amends dmends triadic amend triadic dmend tetradic amend tetradic dmend bitwise verbs band bnot bor bxor casts cast repr flip sv vs serialization compression conditional verbs cond vector conditional and cond or cond database input output reading writing concept projecting files concept execution flow load defn eval reagent react spawn top get close sleep yield return exit kill panic i o verbs set get write read readln print println show 0n display indexing verbs at dot apply list verbs count distinct enlist pick fill filter first last reverse rotate shift take drop cut o cut til logical verbs not or and where math verbs negate monadic division division mod division remainder abs absolute value ceil floor frac min max round more math functions relational verbs lt lt equal match lt not equal null handling set verbs intersection difference union in contains string manipulation like ss str search ssr str search and replace parse format o lower o upper system argv getenv setenv system os type verbs internal type id type typespec internal type id o typedesc other verbs key meta quote rc reference count mv move timestamp value iterators queries select where distinct group limit order join union upsert update delete sql like syntax ptables support dynamic parsers language idioms standard library overview core o core functions for tables for partition tables htreq o http o json o lit o markdown o prolog o repl o sql o urllib o xml o plugins overview customers plugins plugin crypto plugin ctrlc plugin fs plugin kdb plugin serde for python developers for kdb developers application examples faq contributors contacts introduction column based and time series databases are the most intensively developed kind of databases especially during the last decade many products of that sort emerged to meet opportunities created by explosive growth of amounts of data generated by humankind the platform among the others is an effort to create a compact convenient and high performant environment to process analyze and store both real time and historical data it reflects a vision of its developers of how proven and widely used products should develop to fit modern requirements what is the platform the platform is a columnar database engine designed from the ground up to handle both real time streaming data and historical time series workloads unlike traditional row oriented databases the platform stores data in columns enabling highly efficient compression simd accelerated scans and cache friendly access patterns it is built with rust and the o language a modern vector programming language inspired by the array processing tradition of apl k and q the platform serves as a kdb alternative for teams that need real time analytics without the licensing costs and complexity of legacy systems it is designed to run on commodity hardware while delivering performance competitive with specialized in memory databases key features columnar storage and compression data is stored column by column enabling type specific compression algorithms that dramatically reduce storage requirements and improve query throughput sorted partitioned and indexed columns allow sub millisecond lookups even on datasets with billions of rows o language the platform ships with o a concise vector programming language o provides first class support for tables time series operations sql like queries and functional programming its terse syntax allows analysts and engineers to express complex transformations in a few lines of code simd and multithreaded execution queries are automatically parallelized across available cpu cores inner loops use simd instructions for operations such as filtering aggregation and arithmetic on large arrays this ensures that the platform fully utilizes modern multicore processors real time and historical data the platform supports both in memory real time tables and memory mapped historical partitions streaming inserts pub sub messaging and on disk persistence work together seamlessly making it suitable for applications that require both low latency ingestion and deep historical queries built with rust core components are implemented in rust providing memory safety zero cost abstractions and predictable performance without garbage collection pauses use cases financial market data tick by tick storage and analysis of quotes trades and order book snapshots with nanosecond precision timestamps iot and sensor networks ingesting millions of data points per second from distributed sensors with real time dashboards and anomaly detection log and event analytics storing and querying structured log data for observability performance monitoring and security analysis scientific and quantitative research interactive exploration of large numerical datasets using vector operations and ad hoc queries quick start tutorial o language reference queries built served by the platform with ️ to o language 2026 theplatform