Manticore Search Integrations

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google’s data cloud, BigQuery allows you to simplify data integration, cost effectively and securely scale analytics, share rich data experiences with built-in business intelligence, and train and deploy ML models with a simple SQL interface, helping to make your organization’s operations more data-driven. Gemini in BigQuery offers AI-driven tools for assistance and collaboration, such as code suggestions, visual data preparation, and smart recommendations designed to boost efficiency and reduce costs. BigQuery delivers an integrated platform featuring SQL, a notebook, and a natural language-based canvas interface, catering to data professionals with varying coding expertise. This unified workspace streamlines the entire analytics process.

MySQL is the world's most popular open source database. With its proven performance, reliability, and ease-of-use, MySQL has become the leading database choice for web-based applications, used by high profile web properties including Facebook, Twitter, YouTube, and all five of the top five websites*. Additionally, it is an extremely popular choice as embedded database, distributed by thousands of ISVs and OEMs.

Intelligence and security are built into Microsoft SQL Server 2019. You get extras without extra cost, along with best-in-class performance and flexibility for your on-premises needs. Take advantage of the efficiency and agility of the cloud by easily migrating to the cloud without changing code. Unlock insights and make predictions faster with Azure. Develop using the technology of your choice, including open source, backed by Microsoft's innovations. Easily integrate data into your apps and use a rich set of cognitive services to build human-like intelligence across any scale of data. AI is native to the data platform—you can unlock insights faster from all your data, on-premises and in the cloud. Combine your unique enterprise data and the world's data to build an intelligence-driven organization. Work with a flexible data platform that gives you a consistent experience across platforms and gets your innovations to market faster—you can build your apps and then deploy anywhere.

ClickHouse is a fast open-source OLAP database management system. It is column-oriented and allows to generate analytical reports using SQL queries in real-time. ClickHouse's performance exceeds comparable column-oriented database management systems currently available on the market. It processes hundreds of millions to more than a billion rows and tens of gigabytes of data per single server per second. ClickHouse uses all available hardware to its full potential to process each query as fast as possible. Peak processing performance for a single query stands at more than 2 terabytes per second (after decompression, only used columns). In distributed setup reads are automatically balanced among healthy replicas to avoid increasing latency. ClickHouse supports multi-master asynchronous replication and can be deployed across multiple datacenters. All nodes are equal, which allows avoiding having single points of failure.

More customers pick Amazon Redshift than any other cloud data warehouse. Redshift powers analytical workloads for Fortune 500 companies, startups, and everything in between. Companies like Lyft have grown with Redshift from startups to multi-billion dollar enterprises. No other data warehouse makes it as easy to gain new insights from all your data. With Redshift you can query petabytes of structured and semi-structured data across your data warehouse, operational database, and your data lake using standard SQL. Redshift lets you easily save the results of your queries back to your S3 data lake using open formats like Apache Parquet to further analyze from other analytics services like Amazon EMR, Amazon Athena, and Amazon SageMaker. Redshift is the world’s fastest cloud data warehouse and gets faster every year. For performance intensive workloads you can use the new RA3 instances to get up to 3x the performance of any cloud data warehouse.

Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture. Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys. Druid creates inverted indexes for string values for fast search and filter. Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures.

JSON (JavaScript Object Notation) is a lightweight data-interchange format. It is easy for humans to read and write. It is easy for machines to parse and generate. It is based on a subset of the JavaScript Programming Language Standard ECMA-262 3rd Edition - December 1999. JSON is a text format that is completely language independent but uses conventions that are familiar to programmers of the C-family of languages, including C, C++, C#, Java, JavaScript, Perl, Python, and many others. These properties make JSON an ideal data-interchange language. JSON is built on two structures: 1. A collection of name/value pairs. In various languages, this is realized as an object, record, struct, dictionary, hash table, keyed list, or associative array. 2. An ordered list of values. In most languages, this is realized as an array, vector, list, or sequence. These are universal data structures. Virtually all modern programming languages support them in one form or another.

AWS Marketplace is a curated digital catalog that enables customers to discover, purchase, deploy, and manage third-party software, data products, AI agents, and services directly within the AWS ecosystem. It provides access to thousands of listings across categories like security, machine learning, business applications, and DevOps tools. With flexible pricing models such as pay-as-you-go, annual subscriptions, and free trials, AWS Marketplace simplifies procurement and billing by integrating costs into a single AWS invoice. It also supports rapid deployment with pre-configured software that can be launched on AWS infrastructure. This streamlined approach allows businesses to accelerate innovation, reduce time-to-market, and maintain better control over software usage and costs.

PostgreSQL is a powerful, open-source object-relational database system with over 30 years of active development that has earned it a strong reputation for reliability, feature robustness, and performance. There is a wealth of information to be found describing how to install and use PostgreSQL through the official documentation. The open-source community provides many helpful places to become familiar with PostgreSQL, discover how it works, and find career opportunities. Learm more on how to engage with the community. The PostgreSQL Global Development Group has released an update to all supported versions of PostgreSQL, including 15.1, 14.6, 13.9, 12.13, 11.18, and 10.23. This release fixes 25 bugs reported over the last several months. This is the final release of PostgreSQL 10. PostgreSQL 10 will no longer receive security and bug fixes. If you are running PostgreSQL 10 in a production environment, we suggest that you make plans to upgrade.

C++ is a simple and clear language in its expressions. It is true that a piece of code written with C++ may be seen by a stranger of programming a bit more cryptic than some other languages due to the intensive use of special characters ({}[]*&!|...), but once one knows the meaning of such characters it can be even more schematic and clear than other languages that rely more on English words. Also, the simplification of the input/output interface of C++ in comparison to C and the incorporation of the standard template library in the language, makes the communication and manipulation of data in a program written in C++ as simple as in other languages, without losing the power it offers. It is a programming model that treats programming from a perspective where each component is considered an object, with its own properties and methods, replacing or complementing structured programming paradigm, where the focus was on procedures and parameters.