Product Overview
DolphinDB is a high performance time-series database. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. DolphinDB offers operational simplicity, scalability, fault tolerance, and concurrency.
DolphinDB greatly reduces the total cost of ownership of a big data management and analytics system. Instead of using multiple systems from different vendors, clients benefit from DolphinDB’s comprehensive solution with unparalleled performance and low maintenance costs. DolphinDB can be deployed in Linux or Windows environment, on a single node or a cluster, on premises or to the cloud.
Key Benefits
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One-stop SolutionConveniently store, query, analyze and visualize huge volumes of historical and real-time streaming data in a unified system.
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High PerformanceProcess and analyze huge volumes of data at blazing-fast speeds. Conduct extremely high throughput and low latency stream processing with real-time data.
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Rapid DevelopmentHybrid programming paradigm greatly simplifies coding and boosts development speed. Most operations can be written with SQL statements.
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Lower CostSimple syntax expands user base and produces easily readable code that can be conveniently maintained. One stop solution reduces the number of data copies needed.
Key Functionalities
- High-performance Database
- Fully-featured Scripting Language
- Scalable Distributed Computing
- Real-time Data Streaming
- Easy Access
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- High-performance Database
- Columnar hybrid (in-memory and disk-based) engine delivers fast performance for data warehouses with vast amount of data
- Extended functionalities with user defined functions and plugins
- Support millions of partitions for a table
- In-database analytics: complicated computing can be executed within the database
- Native support for processing time series data with up to nanosecond precision
- Standard SQL with enhancements, such as bi-temporal joins (asof join, window join), window functions, pivoting, composite columns, etc
- Table co-location for fast join
- Data compression
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- Fully-featured Scripting Language
- Highly expressive and powerful. Support imperative programming, functional programming, vector programming, SQL programming, and RPC (remote procedure call) programming
- Easy to learn. The syntax is very similar to SQL and Python
- Over 400 built-in functions for various data types (number, temporal, string), data structures (vector, matrix, set, dictionary, table), and system calls (file, database, distributed computing)
- Extended functionalities with user defined functions and plugins
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- Scalable Distributed Computing
- High speed distributed computing through in-memory engine, data localization, fine-grained data partitioning, and parallel computing
- Support various computing models such as pipeline, map-reduce, and iterative computing
- Provide snapshot isolations on computing of distributed dynamic data
- Boost system throughput by sharing data copies in memory among multiple jobs
- Analyze distributed data conveniently. Can write script on one node to execute on the entire cluster instantly without the need of compilation and deployment
- Automatic data replica management for load balance and fault tolerance with embedded distributed file system
- Convenient horizontal scaling on both storage capacity and computing capacity
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- Real-time Data Streaming
- First-class support for stream-table duality. Publishing a message is equivalent to inserting a row to a table. Can use SQL queries on local or distributed stream data
- Handle incoming messages with user defined functions
- Deliver messages with sub-millisecond latency
- Update historical data warehouse with live data with sub-second delay
- Replay historical messages from arbitrary offset
- Provide configurable building blocks (e.g. partition, worker, queue) for traffic control and performance tuning
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- Ease of Use
- Embedded web interface for cluster management, performance monitoring and data access
- Portable IDE (Integrated Development Environment) for data analysis
- Programming APIs for C++, C#, Java, Python, and Excel
- Concurrent user access. Each user works with assigned privileges in an isolated session
- System monitoring via built-in functions, web interface, or Prometheus
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