Best Relational Database in Canada

Teradata VantageCloud is a cloud-native relational database platform built for enterprise-scale performance and analytics. It supports ANSI SQL and relational data models, enabling complex queries across structured and semi-structured data. VantageCloud runs on multi-cloud and hybrid environments, offering elastic scalability, workload optimization, and integration with open-source tools. Its architecture ensures high availability, strong governance, and compatibility with modern data ecosystems—making it ideal for organizations seeking a powerful RDBMS that combines traditional reliability with advanced analytics and AI capabilities.

TeamDesk is the leading AI-enhanced Low-Code database platform for creating powerful and flexible web-based databases with AI assisted development and AI-enhanced data analysis. AI-Assisted Development streamlines database design, no coding, no technical skills required. AI-enhanced Data Analysis empowers business owners and citizen developers with an advanced AI-assisted mechanism to manage and analyze their business data. TechRadar named TeamDesk as the best database platform of the year. TeamDesk online database software is fully scalable and customizable to accommodate customers’ ever evolving business needs, from small companies to large enterprises, from specific manufactures to vertical business integration. TeamDesk provides: AI-Assisted Development AI-enhanced Data Analysis API, Web hooks, Zapier unlimited data storage, records, tables and fields Try it now risk-free and unleash a full potential of AI-assisted development and AI-enhanced data analysis!

KS DB Merge Tools is an easy to use diff & merge tool for MySQL, MariaDB, Oracle Database, SQL Server, PostgreSQL, SQLite, MS Access and Cross-DBMS databases allowing to compare and sync both schema and data. Starting with a schema changes summary, results can be narrowed down to object lists of particular object type (table definitions, views, etc.), and then down to definition of particular object. Data changes can be retrieved as a high-level list of changes totals across all tables in the database, each total row count can be observed as a side-by-side list of rows for the given table, each changed row can be analyzed for changes in each column. Various diff results provide quick filters to show only new/changed/new+changed items (schema objects or table data rows), ability to select required changed items and generate scripts to apply these changes to the other side database. This script can be executed immediately or saved for future use.

Tibero is a relational model-based standard DBMS that has been developed with stable architecture that requires minimal resources from the design step. It allows to efficiently respond to big data processing requests from massive sessions. In addition, it provides a flexible and user-friendly development and easy operating environment based on standards and compatibility. - Multi-Process, multi-thread architecture and various data processing technologies, which support reliable and effective resource management and rapidly process multi-user requests. 1. Shared-disk based active clustering that assures high availability and reliability. 2. Development environment compatibility in compliance with standards.

Serverless, interactive querying for analyzing data in IBM Cloud Object Storage. Query your data directly where it is stored, there's no ETL, no databases, and no infrastructure to manage. IBM Cloud SQL Query uses Apache Spark, an open-source, fast, extensible, in-memory data processing engine optimized for low latency and ad hoc analysis of data. No ETL or schema definition needed to enable SQL queries. Analyze data where it sits in IBM Cloud Object Storage using our query editor and REST API. Run as many queries as you need; with pay-per-query pricing, you pay only for the data scan. Compress or partition data to drive savings and performance. IBM Cloud SQL Query is highly available and executes queries using compute resources across multiple facilities. IBM Cloud SQL Query supports a variety of data formats such as CSV, JSON and Parquet, and allows for standard ANSI SQL.

Save time & costs by streamlining data pipelines with zero-maintenance open source solutions. From ingestion to visualization, all are integrated, fully managed, and highly reliable, so your engineers will love working with data. You choose whether to use any of DoubleCloud’s managed open source services or leverage the full power of the platform, including data storage, orchestration, ELT, and real-time visualization. We provide leading open source services like ClickHouse, Kafka, and Airflow, with deployment on Amazon Web Services or Google Cloud. Our no-code ELT tool allows real-time data syncing between systems, fast, serverless, and seamlessly integrated with your existing infrastructure. With our managed open-source data visualization you can simply visualize your data in real time by building charts and dashboards. We’ve designed our platform to make the day-to-day life of engineers more convenient.

IBM Informix® is a fast and flexible database with the ability to seamlessly integrate SQL, NoSQL/JSON, and time series and spatial data. Its versatility and ease of use make Informix a preferred solution for a wide range of environments, from enterprise data warehouses to individual application development. Also, with its small footprint and self-managing capabilities, Informix is well suited for embedded data-management solutions. IoT data demands robust processing and integration capabilities. Informix offers a hybrid database system with minimal administrative requirements and memory footprint combined with powerful functionality. Key features make Informix ideal for multi-tiered architectures that require processing at the device level, at gateway layers and in the cloud. Native encryption to protect data at rest and in motion. Support for flexible schema, multiple APIs and configurations.

The enterprise database for time series, documents, and vectors. Store any type of data and combine the simplicity of SQL with the scalability of NoSQL. CrateDB is an open source distributed database running queries in milliseconds, whatever the complexity, volume and velocity of data.

Offers the complete feature set of Informix on-premises deployments with less cost, complexity and risk than managing your own infrastructure. The IBM® Informix® on Cloud offering provides an Informix database on IBM Cloud®. It offers customers the rich features of an on-premises Informix deployment while helping reduce the cost, complexity and risk of managing your own infrastructure. Informix on Cloud brings you a high-performance engine that integrates time series, spatial, NoSQL and SQL data together with easy access through MQTT, REST and MongoDB APIs. Accelerate and simplify your cloud deployments with Informix on Cloud and take advantage of the high-performance Informix engine that integrates time series, spatial, NoSQL and SQL data. Help reduce the cost and complexity of infrastructure maintenance using flexible hosting and software licensing options. Choose the size that meets your business needs, with always-on support.

XTDB is an immutable SQL database designed to simplify application development and ensure data compliance. It automatically preserves data history, enabling comprehensive time-travel queries. Users can perform as-of queries and audits using SQL commands. XTDB is trusted by various companies to transform dynamic and temporal applications. It is easy to get started with via HTTP, plain SQL, or various programming languages, requiring only a client driver or Curl. Users can effortlessly insert data immutably, query it across time, and execute complex joins. Risk systems benefit directly from bitemporal modeling. Valid time can be used to correlate out-of-order trade data whilst making compliance easy. Exposing data across an organization is a challenge when things are changing all the time. XTDB simplifies data exchange and can power advanced temporal analysis. Modeling future pricing, tax, and discount changes requires extensive temporal queries.