The Database for
Time & Space
Real-Time Analytics Database
Kinetica's lockless architecture, distributed ingestion, and vectorized query enable you to work with data as it pours in. Kinetica allows for simulataneous ingest and query, and avoids the need for constant re-indexing and re-aggregations as new data changes the picture.
Advanced Geospatial Capabilities
Kinetica is built to track billions of objects as they move in real-time. Over 130 geospatial functions, geo-joins, graph solving and matching makes analytics on spatial and time series data at scale easier and faster.
Lower Cost of Ownership
Kinetica's vectorized design is not just for speed – it enables you to do more with less. More power allows for simpler data structures, which means less time engineering the data, more flexibility for exploring the data, and lower compute costs.
Independent TPC-DS benchmark. Kinetica is over 5000X faster than ClickHouse
Radiant Advisors recently tested Kinetica against the TPC-DS Benchmark Suite. Kinetica was able to execute 98 of 99 queries with "consistent returns", "excellent performance", and "impressive results". Read the Report »
Real Time AnalysisAdd context, trigger alerts and make decisions by fusing streaming data with historical data
Simultaneous Ingest & Query
Kinetica's lockless, distributed architecture enables ingest at speed. And the power of vectorized queries mean there is less need to update indexes before data can be explored.
Real-time
Materialized Views
Join, fuse and aggregate data from streams and static datasets to create real-time representations of constantly evolving data.
Decisioning
and Notifications
Output event streams to Kafka, make decisions, and generate notifications with webhooks. Kinetica enables you to build a genuinely real-time system to monitor changing situations.
Time and Space AnalyticsFor Complex Geospatial & Temporal Questions
Vectorized processing opens the door to amazingly fast analytics and detailed visualization of moving objects at scale.
Geospatial Functions
Work with with geospatial objects (points, shapes, tracks) and take advantage of over 130 vector-enhanced geospatial functions for filtering and joining data by area, by track, custom shapes and more.
Geospatial Analytics »
Visualization Pipeline
Vectorized server-side rendering makes it possible to plot billions of points without bandwidth constraints. Visualizations are rendered as WMS layers, or video, and can be overlaid on maps.
Mapping & Visualization API »
Time Series
Kinetica natively manages time-series data and window functions for efficient time series analysis. Powerful temporal selectors, with ASOF join filters so you can quickly gather data from the past.
Graph Analytics
Create graphs from relational data to optimize routes, match supply and demand, and uncover hidden relationships. Kinetica's flexible graph grammar has feature parity with Cypher.
Graph Analytics »
User Defined Functions
Bring your own custom algorithms or machine learning models to your geospatial data. User Defined Functions (UDFs) enable you to extend Kinetica and make inferences from those models directly alongside your data, rather than moving data out to separate systems for analysis. APIs for C++, Python & Java.
User Defined Functions »
Take a Tour of Kinetica
Kinetica is a delight for administrators and data-engineers to use. Kinetica Workbench provides a sophisticated, yet intuitive interface, to interactively explore data, organize and store SQL workbooks, import and export data streams, and for general database administration.
Lower TCOBetter Performance with Less Infrastructure.
With it's vectorized algorithms, dynamic tiered storage, and reduced need for supporting data structures, Kinetica enables you to do more with fewer resources and less work than comparable systems.
Large US Financial Institution
700-node spark cluster running queries in hours took seconds on 16 nodes of KineticaTop US Retailer
Consolidated 100 nodes of Cassandra(NoSQL) and Spark into 8 Kinetica nodesLarge Pharma
Identical performance between a 88-node Impala cluster and a 6-node Kinetica Intel cluster in AzureQuery, Explore, DiscoverExplore your Data, Manage your Data
Kinetica Workbench
An analytical, administrative and data management interface to Kinetica. Import data or connect to external data stores. Create workbooks for multi-step analysis, visualization and sharing of results.
Write Queries in SQL
Kinetica has broad support for SQL interaction with a mature suite of SQL functionality. This makes it easy for analysts to be productive quickly.
SQL Query Support »
REST & Native API's
Data Scientists and Developers can develop sophisticated applications with REST and Native APIs. Language specific APIs are available for C++, C#, Java, Javascript, NodeJS & Python.
API Documentation »
Works with Popular BI Tools
Kinetica works can connect to a wide range of popular BI tools such as Tableau, Spotfire, PowerBI, ESRI, DBeaver and Grafana for real-time analytics Postgres Wireline compatability or through the ODBC/JDBC connector.
Evolved to Meet the Demands of the Modern Enterprise
Scale Out
Work with petabytes of data at speed with Kinetica's memory-first, fully distributed architecture. Kinetica prioritizes and manages data across VRAM, RAM, disk, and cold storage and can create external tables for working with data in HDFS, S3 and Azure.
Cell-Level Security
Kinetica provides advanced data access controls that let you define dynamic obfuscation, redaction, and access rules down to the column level. Kinetica works out of the box with industry standard external authentication and identity systems like LDAP, Active Directory and Kerberos.
High Availability
Eliminate single points of failure and recover gracefully. Kinetica offers node and process failover for in-cluster resiliency, and multiple clusters may be grouped in a ring resiliency to spread data and ensure eventual consistency.
Administration
Kinetica's administration, installation, and configuration management tools give users an intuitive way to provision cloud hardware, configure cluster security, add/remove nodes, data backup and monitor cluster health.
CASE STUDY
SFEI uses drones to collect thousands of images of the San Francisco Bay, which they feed into a Kinetica-powered machine learning algorithm to detect trash - a process that has gone from days to just hours, so we can identify pollutants and take immediate action.
CASE STUDY
OVO SmartCube is designed to evaluate customer preferences using analytics powered by a machine learning-enabled recommendation engine, which makes product suggestions. Powered by Kinetica, the machine can also provide instant assessments of when and what purchases take place, in order to offer relevant deals.
Book a Demo!
Sometimes marketing copy can sound too good to be true. The best way to appreciate the possibilities that Kinetica brings to large-scale geospatial analytics is to see it in action, or try it with your own data, your own schemas and your own queries.
Contact us, and we can set you up with a demo and a trial environment for you to experience it for yourself.