#Caché

Executive Summary

The best way to compare the performance of database products is in a head-to-head test using a real application, preferably one of your own. This is especially true when evaluating Caché's post-relational technology, because "standard" transaction processing benchmarking methodologies assume the restrictive "row and columns" format of a relational database. They cannot accurately predict the performance of real applications, which often use complex data models.

Abstract

The European Space Agency (ESA) has chosen InterSystems Caché as the database technology for the AGIS astrometric solution that will be used to analyze the celestial data captured by the Gaia satellite.

The Gaia mission is to create an accurate phase-map of about a billion celestial objects. During the mission, the AGIS solution will iteratively refine the accuracy of Gaia's spatial observations, ultimately achieving accuracies that are on the order of 20 microarcseconds.

Abstract

A benchmark of a real-world application, which loads data into a data warehouse for subsequent analysis, was performed. To conduct the benchmark, one module of the Oracle-based application was replicated in Caché ObjectScript. Only about 40 person-hours of work was required to duplicate the functionality of the original module in Caché.

The time required to complete certain tasks was measured running the Caché-based module, and was compared to existing data.

Introduction

If the administrators responsible for securing applications had their way, passwords would be long complex strings of random symbols, and users would memorize different passwords for every application they use. But in the real world, few people are capable of such prodigious feats of memory. The typical user can only remember a handful of relatively short passwords.

That’s why an increasing number of applications are requiring two-factor authentication.

Providing a reliable infrastructure for rapid, unattended, automated failover

Technology Overview

Traditional availability and replication solutions often require substantial capital investments in infrastructure, deployment, configuration, software licensing, and planning. Caché Database Mirroring (Mirroring) is designed to provide an economical solution for rapid, reliable, robust, automatic failover between two Caché systems, making mirroring the ideal automatic failover high-availability solution for the enterprise.

Introduction

This document is intended to provide a survey of various High Availability (HA) strategies that can be used in conjunction with InterSystems Caché, Ensemble, and HealthShare Foundation. This document also provides an overview of the various types of system outages that can occur, as well as how each strategy would handle a given outage, with the goal of helping you choose the right strategy for your specific deployment.

Introduction

Impedance mismatch is a term commonly used to describe the problem of an object-oriented (OO) application housing its data in legacy relational databases (RDBMS). C++ programmers have dealt with it for years, and it is now a familiar problem to Java and other OO programmers.

Impedance mismatch arises from the inherent lack of affinity between the object and relational models.

InterSystems Caché 2015.1 soars from 6 million to more than 21 million end-user database accesses per second on the Intel® Xeon® processor E7 v2 family compared to Caché 2013.1 on the Intel® Xeon® processor E5 family

Overview

With data volumes soaring and the opportunities to derive value from data rising, database scalability has become a crucial challenge for a wide range of industries. In healthcare, the rising demands for healthcare services and significant changes in the regulatory and business climates can make the challenges particularly acute.

Providing a reliable infrastructure for rapid, unattended, automated failover

Technology Overview

Traditional availability and replication solutions often require substantial capital investments in infrastructure, deployment, configuration, software licensing, and planning. Caché Database Mirroring (Mirroring) is designed to provide an economical solution for rapid, reliable, robust, automatic failover between two Caché systems, making mirroring the ideal automatic failover high-availability solution for the enterprise.

Abstract

A global provider of mobile telecommunications software tested the performance of InterSystems Caché and Oracle as the database in a simulated data mart application. They found Caché to be 41% faster than Oracle at building a data mart. When testing the response time to SQL queries of the data mart, Caché's performance ranged from 1.8 times to 513 times faster than Oracle.

Introduction

Telecommunications companies, because they generate and must analyze enormous amounts of information, are among the most demanding database users in the world.

Introduction

With the maturation and wide acceptance of Java, object-oriented programming has moved to the foreground of the application development landscape. Because of their rich data models and support for productivity-enhancing concepts such as encapsulation, inheritance, and polymorphism, object technologies like Java, C++, and COM, are favored by today's application developers.

However, much of the world's data still resides in relational databases.

Introduction

Experts estimate that 85% of all data exists in unstructured formats – held in e-mails, documents (contracts, memos, clinical notes, legal briefs), social media feeds, etc. Where structured data typically accounts for quantitative facts, the more interesting and potentially more valuable expert opinions and conclusions are often hidden in these unstructured formats. And with massive volumes of text being generated at unprecedented speed, there’s very little chance this information can be made useful without some process of synthesis or automation.

Introduction

To overcome the performance limitations of traditional relational databases, applications - ranging from those running on a single machine to large, interconnected grids - often use in-memory databases to accelerate data access. While in-memory databases and caching products increase throughput, they suffer from a number of limitations including lack of support for large data sets, excessive hardware requirements, and limits on scalability.

Executive Overview

One way financial services firms can improve their operational efficiency is to revamp their data management infrastructure. Creating a central repository for data that is used by multiple applications can ensure data consistency and quality across the enterprise, ease integration bottlenecks, and lower the number of failed trades.However, different applications have different database usage patterns.

Customers who switch to Caché from relational databases report that their average performance is up to 20 time faster, running on the same hardware, with no changes to the application. What is it about Caché that lets applications run so fast?

Introduction

By now, anybody working in the technology sector will have heard of Cloud computing. But the concept is increasingly being paid attention to outside of IT departments, with growing recognition among boardlevel executives of the potential of this range of innovations. Frequently, senior personnel are hearing stories about how the Cloud helps organizations reduce costs, boost efficiency and expand their operations, so they’ll be excited about what the Cloud can do for them.

As a result, Cloud is one of the fastest-growing parts of the IT industry.

Abstract

In a recent benchmark test of an application based on InterSystems Caché, a sustainable rate of 8.9million database accesses/second, with peaks of 16.9 million database accesses/second, was achieved. These results were from a test performed on a connected system of eight applications servers, using Intel Xeon 5570 processors, and running Linux as the operating system. This benchmark shows that:

1. Caché can achieve unheard of levels of performance for an object database. It provides full persistence of data at speeds that are normally only reached by in-memory databases.

Introduction

With the growing popularity of smart phones and tablet computers, consumers are coming to expect that software solutions will be presented as "apps" on their mobile devices. The challenge for most application developers is to find ways to make their existing solutions run on modern mobile platforms without incurring the delay and cost of a complete rewrite.