Search Results for "self-extracing"

Built for the modern Python Data Science ecosystem, ArcticDB transforms your ability to handle complex real-world data with an Incredibly fast proven Petabyte scale. ArcticDB is designed with quant users in mind. It allows you to self-manage your data leveraging your preferred infrastructure. Giving you the keys to protect your most valuable asset. Supports large concurrent writes to many tables ensuring datasets can be onboarded fast and in the most convenient format. Scale-out architecture and built-in compression ensure that networks and storage are utilized efficiently. ...

Did you ever want to store your MATLAB(R) data in a SQL database? Nothing large, simply a few array or strutures in a few tables. Maybe a few indicies and everything manageable with SQL commands? Then msqlite will be the right choice for you! mksqlite connects the power of MATLAB(R) with the efficiency of the SQLite database engine. (See also https://github.com/AndreasMartin72/mksqlite)

...The system will support automated physical database design (e.g., indexes, materialized views, sharding), knob configuration tuning, SQL tuning, and hardware capacity/scaling. Our research focuses on building the system components that support such self-driving operations with little to no human guidance. We seek to create a system that not only able to optimize the current workload, but also to predict future workload trends and prepare itself accordingly. Our plan is for NoisePage to support the most common database tuning techniques without requiring humans to determine the right way and proper time to deploy them. ...

...Client API supports including C++, PHP, Python, Cpy, Java, nodejs, Ruby, Go(see all). Persistent queue service. Replication(master-slave), load balance. GUI administration tool(phpssdbadmin). Built-in CLI nagios self-checks. Benchmarks are taken by ssdb-bench(SSDB) and redis-benchmark(Redis). SSDB is licensed under New BSD License, a very flexible license to use. Drag the static libraies files into your iOS project. Then add ios/include to your iOS project's Header Search Paths, which is set in Build Settings.

This is a comprehensive C++ wrapper for the LMDB embedded database library, offering both an error-checked procedural interface and an object-oriented resource interface with RAII semantics. • Designed to be entirely self-contained as a single <lmdb++.h> header file that can be dropped into a project. • Implements a straightforward mapping from C to C++, with consistent naming. • Provides both a procedural interface and an object-oriented RAII interface. • Simplifies error handling by translating error codes into C++ exceptions. • Carefully differentiates logic errors, runtime errors, and fatal errors...