Best Query Engines for Windows of 2025

You can create flat or relational databases with unlimited fields, tables, and rows. A custom report builder is included. Create custom reports by connecting to compatible ODBC databases. You can create your own databases. Here are some highlights: Filter tables instantly - Ultra simple graphical-user-interface - One-click table and data form creation - You can open up to 5 databases simultaneously Export your data to comma-separated files - Create custom reports to all your databases - A complete helpfile for creating database reports - You can print tables and queries directly from your data grid - Supports any SQL standard your ODBC compatible databases require For best performance and user experience, please install and run this database app with full administrator rights. Requirements: . 1024x768 Display Size . Windows 98 / XP / Windows 8 / Windows 10 - 32bit or 64bit No Java or DotNet are required. Green Energy Software. One step at a time, saving the planet

Trino is a remarkably fast query engine designed to operate at exceptional speeds. It serves as a high-performance, distributed SQL query engine tailored for big data analytics, enabling users to delve into their vast data environments. Constructed for optimal efficiency, Trino excels in low-latency analytics and is extensively utilized by some of the largest enterprises globally to perform queries on exabyte-scale data lakes and enormous data warehouses. It accommodates a variety of scenarios, including interactive ad-hoc analytics, extensive batch queries spanning several hours, and high-throughput applications that require rapid sub-second query responses. Trino adheres to ANSI SQL standards, making it compatible with popular business intelligence tools like R, Tableau, Power BI, and Superset. Moreover, it allows direct querying of data from various sources such as Hadoop, S3, Cassandra, and MySQL, eliminating the need for cumbersome, time-consuming, and error-prone data copying processes. This capability empowers users to access and analyze data from multiple systems seamlessly within a single query. Such versatility makes Trino a powerful asset in today's data-driven landscape.

PuppyGraph allows you to effortlessly query one or multiple data sources through a cohesive graph model. Traditional graph databases can be costly, require extensive setup time, and necessitate a specialized team to maintain. They often take hours to execute multi-hop queries and encounter difficulties when managing datasets larger than 100GB. Having a separate graph database can complicate your overall architecture due to fragile ETL processes, ultimately leading to increased total cost of ownership (TCO). With PuppyGraph, you can connect to any data source, regardless of its location, enabling cross-cloud and cross-region graph analytics without the need for intricate ETLs or data duplication. By directly linking to your data warehouses and lakes, PuppyGraph allows you to query your data as a graph without the burden of constructing and maintaining lengthy ETL pipelines typical of conventional graph database configurations. There's no longer a need to deal with delays in data access or unreliable ETL operations. Additionally, PuppyGraph resolves scalability challenges associated with graphs by decoupling computation from storage, allowing for more efficient data handling. This innovative approach not only enhances performance but also simplifies your data management strategy.

SPListX for SharePoint is an advanced application that uses a rule-based query engine to facilitate the exportation of document and picture library contents along with their metadata and related list items, including file attachments, directly to the Windows File System. With SPListX, users can export an entire SharePoint site, encompassing libraries, folders, documents, list items, version histories, metadata, and permissions, to their preferred location within the Windows File System. This versatile tool is compatible with various versions of SharePoint, including 2019, 2016, 2013, 2010, 2007, 2003, as well as Office 365, making it a reliable choice for organizations utilizing different SharePoint environments. Its comprehensive support for multiple SharePoint versions ensures that users can efficiently manage and transfer their data regardless of the specific SharePoint setup they are employing.

Impala delivers rapid response times and accommodates a high number of concurrent users for business intelligence and analytical queries within the Hadoop ecosystem, supporting frameworks like Iceberg, various open data formats, and numerous cloud storage solutions. It is designed to scale seamlessly, even in environments that host multiple tenants. Additionally, Impala integrates with native Hadoop security protocols and utilizes Kerberos for authentication, while the Ranger module allows for precise user and application authorization based on the data they need to access. This means you can leverage the same file formats, data structures, security measures, and resource management systems as your existing Hadoop setup, eliminating the need for redundant infrastructure or unnecessary data transformations. For those already using Apache Hive, Impala is compatible, sharing the same metadata and ODBC driver, which streamlines the transition. Just like Hive, Impala employs SQL, thereby alleviating the need to develop new implementations. With Impala, a greater number of users can engage with a wider array of data via a unified repository, ensuring that valuable insights are accessible from the source to analysis without compromising on efficiency. Ultimately, this makes Impala an essential tool for organizations looking to enhance their data interaction capabilities.

QuasarDB, the core of Quasar's intelligence, is an advanced, distributed, column-oriented database management system specifically engineered for high-performance timeseries data handling, enabling real-time processing for massive petascale applications. It boasts up to 20 times less disk space requirement, making it exceptionally efficient. The unmatched ingestion and compression features of QuasarDB allow for up to 10,000 times quicker feature extraction. This database can perform real-time feature extraction directly from raw data via an integrated map/reduce query engine, a sophisticated aggregation engine that utilizes SIMD capabilities of contemporary CPUs, and stochastic indexes that consume minimal disk storage. Its ultra-efficient resource utilization, ability to integrate with object storage solutions like S3, innovative compression methods, and reasonable pricing structure make it the most economical timeseries solution available. Furthermore, QuasarDB is versatile enough to operate seamlessly across various platforms, from 32-bit ARM devices to high-performance Intel servers, accommodating both Edge Computing environments and traditional cloud or on-premises deployments. Its scalability and efficiency make it an ideal choice for businesses aiming to harness the full potential of their data in real-time.

Don't let game, app, or device crashes stop you from having a great experience. Backtrace automates cross-platform exception management and cross-platform crash management so that you can focus on shipping. Cross-platform callstack, event aggregation, and monitoring. A single system can process errors from panics and core dumps, minidumps, as well as during runtime across your stack. Backtrace generates searchable, structured error reports from your data. Automated analysis reduces time to resolution by surfacing important signals which lead engineers to the crash root cause. Rich integrations into dashboards and notification systems mean that you don't have to worry about missing a detail. Backtrace's rich queries engine will help you answer the questions that are most important to you. A high-level overview of errors, prioritization and trends across all projects can be viewed. You can search through key data points as well as your own custom data for all errors.