OneTick Release 1.19 is now available on our download site.
OneTick 1.19 introduces support for distributed loading on public (AWS and GCP, with Azure support coming later) or private server clusters. We are also offering elastic computing on AWS in 1.19.
In addition our new release improves performance and enhances user experience with Query Designer, Python Query API and OneTick Dashboards:
- Distributed loading using public (AWS and GCP; Azure support coming later) or private clusters allows to dramatically decrease the time to load large daily archives (such as OPRA) or reload years’ worth of enriched TCA datasets when input parameters change.
- OneTick 1.19 introduces support for elastic computing on AWS. We are planning to add full query auto-scaling, and similar functionality for GCP and Azure soon.
- Customers who upgrade to Release 1.19 will be able to load time series of virtually unlimited size, important when loading data sets such as CME.
- OneTick Dashboard designers can now validate data in TextInput widget, perform OS actions using the new System widget and display trades on the OrderBook widget. Dashboard analysts can now search for data in Data Grids, use colors in TreeMap widget and display gaps in charts for better visual impact of their Dashboards.
In addition, OneTick 1.19 introduces new features requested by our customers:
- Integration with Kafka using Protobuf, Avro (coming soon) and OneTick native message formats.
- Integration with Apache Parquet for enhanced interoperability with 3rd party products such as Impala, Hive and Spark.
- New OneTick Multicast Collector API natively supports multicast feeds including retransmission. We have already written OPRA, CTA and UTP collectors using this new API.
- OneTick now supports Decimal data type that provides high precision arithmetic important for processing cryptocurrency datasets and other use cases.
- Python API enhancements: OneTick introduced a two-way OTQ Query-to-Python conversion tool for improved query development and code management. Python Query API now supports multi-staged queries, nanosecond timestamp granularity, multiple queries per file. Supported Python versions: 2.6 - 3.7 (new).