Best Data Management Software for Google Cloud BigQuery

BigLake is a storage platform that unifies data warehouses, lakes and allows BigQuery and open-source frameworks such as Spark to access data with fine-grained control. BigLake offers accelerated query performance across multicloud storage and open formats like Apache Iceberg. You can store one copy of your data across all data warehouses and lakes. Multi-cloud governance and fine-grained access control for distributed data. Integration with open-source analytics tools, and open data formats is seamless. You can unlock analytics on distributed data no matter where it is stored. While choosing the best open-source or cloud-native analytics tools over a single copy, you can also access analytics on distributed data. Fine-grained access control for open source engines such as Apache Spark, Presto and Trino and open formats like Parquet. BigQuery supports performant queries on data lakes. Integrates with Dataplex for management at scale, including logical organization.

Data analysts can now gain insights faster and without any barriers. Intelligent data stack automation, gain insights from your data 10x quicker with AI. Intelligence for the modern data-stack has arrived, a technology that was developed at Stanford's AI lab and is now available to enterprises. Use natural language to extract value from your messy data, complex and siloed in minutes. Tell your data what you want and it will generate code to execute. Automate complex data tasks in a way that is specific to your company and not covered by templated solutions. Automate data-intensive workflows using the modern data stack. Discover insights in minutes and not months. Uniquely designed and tuned to your organization's requirements. Snowflake, Databricks Redshift, BigQuery and more are integrated with dbt.

View the impact of data issues in real time without running SQL. We analyze your logs to identify freshness anomalies and volume, schema changes, pipeline errors and their impact on your business. Masthead monitors each table, script, process and dashboard in your data warehouse, as well as the connected BI tools, for anomalies. It alerts data teams in real-time if data failures happen. Masthead shows data anomalies, pipeline errors and their implications on data consumers. Masthead maps lineage data issues, so you can troubleshoot in minutes, not hours. It was a game changer for us to get a comprehensive overview of all processes within GCP without having to give access our data. It saved us time and money. You can now see the cost of every pipeline in your cloud, irrespective of whether it is ETL. Masthead has AI-powered recommendations that can help you optimize your queries and models. Masthead can be connected to your data warehouse in 15 minutes.

DataLakeHouse.io Data Sync allows users to replicate and synchronize data from operational systems (on-premises and cloud-based SaaS), into destinations of their choice, primarily Cloud Data Warehouses. DLH.io is a tool for marketing teams, but also for any data team in any size organization. It enables business cases to build single source of truth data repositories such as dimensional warehouses, data vaults 2.0, and machine learning workloads. Use cases include technical and functional examples, including: ELT and ETL, Data Warehouses, Pipelines, Analytics, AI & Machine Learning and Data, Marketing and Sales, Retail and FinTech, Restaurants, Manufacturing, Public Sector and more. DataLakeHouse.io has a mission: to orchestrate the data of every organization, especially those who wish to become data-driven or continue their data-driven strategy journey. DataLakeHouse.io, aka DLH.io, allows hundreds of companies manage their cloud data warehousing solutions.

Reframe your perception of time with data analytics. Instantly access the data of your business and work directly in your dashboard, without having to go back and forth with your IT team. Indexima DataHub is a new space where operational and functional users can instantly access their data. Indexima's unique indexing engine, combined with machine learning, allows businesses to quickly and easily access their data. The robust and scalable solution allows businesses to query their data directly from the source in volumes of up to tens billions of rows within milliseconds. With our Indexima platform, users can implement instant analytics for all their data with just one click. Indexima’s new ROI and TCO Calculator will help you determine the ROI of your data platform in just 30 seconds. Infrastructure costs, project deployment times, and data engineering cost, while boosting analytical performances.

The toolkit to build interactive, fully customized analytics experiences into your apps. Embeddable believes that you shouldn't be forced to choose between buying or building your analytics solution. While creating charts, graphs and dashboards is an expensive, ongoing commitment, the out-of-the box solutions do not deliver the user experience that you desire for your clients. Welcome to the world of limitless creativity where you can create analytics experiences that are truly remarkable, and surpass your customers' expectations. Create your perfect experience using best-in class open source libraries. Embeddable displays data in your app using a secure read only transaction, regardless of whether your data is stored in a central data warehouse or distributed across multiple microservices. Let your imagination run wild and create the analytics solution you want, without compromising.

Secoda AI can help you generate documentation and queries from your metadata. This will save your team hundreds of hours of tedious work. Secoda AI will also generate documentation and queries based on your metadata. This will save your team hundreds of tedious hours and redundant data requests. Search across all columns, dashboards and metrics, as well as tables, dashboards and tables. AI-powered searches allow you to ask any question and receive a contextual response quickly. Answer questions. Our API allows you to integrate data discovery into your workflow, without disrupting the flow. Perform bulk updates, tag PII, manage tech debt and more. Eliminate manual errors and have complete trust in your knowledge base.

Tabular is a table store that allows you to create an open table. It was created by the Apache Iceberg creators. Connect multiple computing frameworks and engines. Reduce query time and costs up to 50%. Centralize enforcement of RBAC policies. Connect any query engine, framework, or tool, including Athena BigQuery, Snowflake Databricks Trino Spark Python, Snowflake Redshift, Snowflake Databricks and Redshift. Smart compaction, data clustering and other automated services reduce storage costs by up to 50% and query times. Unify data access in the database or table. RBAC controls are easy to manage, enforce consistently, and audit. Centralize your security at the table. Tabular is easy-to-use and has RBAC, high-powered performance, and high ingestion under the hood. Tabular allows you to choose from multiple "best-of-breed" compute engines, based on their strengths. Assign privileges to the data warehouse database or table level.

Unify data from over 100 sources to help your team quickly deliver better insights. Sync data from data warehouses into the business tools that your team prefers. Save up to 75% on your costs by efficiently scaling data operations using a platform that is custom-built for your data teams. You don't want to deal with the hassle of managing your data warehouse? We are the only platform to offer an integrated managed data store that meets all your data management requirements. Choose from a growing list of 100+ fully-managed connectors and 20+ destinations, including SaaS applications, databases, datawarehouses, and many more. Securely manage data movement with granularity. Schedule and transform data for analytics in sync with pipelines.

It is difficult to create and manage data policies. With PACE, you can ensure that data is used in a secure manner. You can apply data policies to code, no matter where it is located. Say goodbye to costly meetings and long waits, and hello to your new open-source data security engine. Data policies aren't only about controlling access, they are also about extracting value from the data with the correct guardrails. PACE allows you to collaborate on the why, and when automating the code. With PACE, you can programmatically apply data policies across multiple platforms. Integrate into your data platform or catalog (optional) and leverage the native capabilities that you already have. PACE automates the application of policies across major data platforms and catalogs, easing your governance processes. Centralize control and decentralize the execution of policies. Auditing obligations can be met by demonstrating how controls are implemented.

Data engineering workflows that are powerful, but without the headaches of infrastructure. Simple, reusable Python is used to define complex streaming, scheduling and data backfill pipelines. Fetch all your data in real time, no matter how complicated. Deep learning and LLMs can be used to make decisions along with structured business data. Don't pay vendors for data that you won't use. Instead, query data right before online predictions. Experiment with Jupyter and then deploy into production. Create new data workflows and prevent train-serve skew in milliseconds. Instantly monitor your data workflows and track usage and data quality. You can see everything you have computed, and the data will replay any information. Integrate with your existing tools and deploy it to your own infrastructure. Custom hold times and withdrawal limits can be set.

Hue provides the best querying experience by combining the most intelligent autocomplete components and query editor. The tables and storage browses use your existing data catalog in a transparent way. Help users find the right data among thousands databases and document it themselves. Help users with their SQL queries, and use rich previews of links. Share directly from the editor in Slack. There are several apps, each specialized in one type of querying. Browsers are the first place to explore data sources. The editor excels at SQL queries. It has an intelligent autocomplete and risk alerts. Self-service troubleshooting is also available. Dashboards are primarily used to visualize indexed data, but they can also query SQL databases. The results of a search for specific cell values are highlighted. Hue has one of the most powerful SQL autocompletes on the planet to make your SQL editing experience as easy as possible.

PeerDB is the fastest, easiest, and most cost-effective solution to replicate data between Postgres and data warehouses, queues and storage. Designed to scale at any size and tailored for data stores. PeerDB replays the schema messages using replication messages from Postgres replication slots. Alerts for slot expansion and connections. Native support for Postgres toast columns and large JSONB for IoT. Optimized query designs to reduce warehouse costs. Especially useful for Snowflake or BigQuery. Support for partitioned table via both publish. Transaction snapshotting and CTID scanning provide a consistent and fast initial load. High-availability with autoscaling, advanced logs, metrics, dashboards and monitoring dashboards.

Tobiko, a data-transformation platform, is backward compatible with databases and ships data faster, more effectively, with fewer errors. Create a development environment without having to rebuild the entire DAG. Tobiko only makes the necessary changes. Do not rebuild the entire page when you add a new column. You already built your change. Tobiko automatically promotes your prod without requiring you to redo any of your work. Avoid debugging clunky Jinja by defining your models in SQL. Tobiko is scalable for startups and enterprises. Tobiko improves developer productivity and understands the SQL that you write by detecting issues at compile time. Audits and data comparisons provide validation, making it easy to trust your datasets. Each change is analyzed, and automatically classified as breaking or not. When mistakes occur, teams can seamlessly rollback to the previous version to reduce production downtime.

PuppyGraph allows you to query multiple data stores in a single graph model. Graph databases can be expensive, require months of setup, and require a dedicated team. Traditional graph databases struggle to handle data beyond 100GB and can take hours to run queries with multiple hops. A separate graph database complicates architecture with fragile ETLs, and increases your total cost ownership (TCO). Connect to any data source, anywhere. Cross-cloud and cross region graph analytics. No ETLs are required, nor is data replication. PuppyGraph allows you to query data as a graph directly from your data lakes and warehouses. This eliminates the need for time-consuming ETL processes that are required with a traditional graph databases setup. No more data delays or failed ETL processes. PuppyGraph eliminates graph scaling issues by separating computation from storage.

Integrate your data sources including relational and NoSQL database, SaaS and APIs. You can query them immediately as a single source of data. Process data wherever you are. Data from different sources can be merged, retrieved, and cached. Use webhooks for streaming data from Kafka or Segment into the Peaka Table. Real-time data access replaces nightly batch ingestion. Treat each data source as a relational database. Convert any API into a table and combine and join it with other data sources. Use familiar SQL to run queries on NoSQL databases. The same skills can be used to retrieve data from SQL and NoSQL database. You can query and filter your consolidated datasets to create new data sets. Use APIs to expose them and serve other apps or systems. Don't get bogged down with scripts and logs when setting up your data stack. Eliminate the burdens of managing and maintaining ETL pipelines.

Seenka integrates organic exposure and paid exposure across digital, traditional, and social media channels to detect opportunities, optimize your campaigns, create a multi-attribution model or discover potential audiences and customers. Control and analyze in real time the integrated offline-online exposure of your brand, competitors, and audiences across all channels that influence customer decision. Create dynamic dashboards to analyze trends within your industry or audience. Discover potential activations, create your 360-attribution model, and identify customers. Sync media data between your analytics platforms (Looker Big Query Spreadsheet) and activation apps such as WhatsApp, Google Ads Meta Ads YouTube. Seenka believes that data should be dynamic and not just a collection of files. Data that anticipates competition, identifies new opportunities and gives you a competitive edge. Put data to work.

DataChain connects your unstructured cloud files with AI models, APIs and foundational models to enable instant data insights. Its Pythonic stack accelerates the development by tenfold when switching to Python-based data wrangling, without SQL data islands. DataChain provides dataset versioning to ensure full reproducibility and traceability for each dataset. This helps streamline team collaboration while ensuring data integrity. It allows you analyze your data wherever it is stored, storing raw data (S3, GCP or Azure) and metadata in inefficient datawarehouses. DataChain provides tools and integrations which are cloud-agnostic in terms of both storage and computing. DataChain allows you to query your multi-modal unstructured data. You can also apply intelligent AI filters for training data and snapshot your unstructured dataset, the code used for data selection and any stored or computed meta data.

Google Cloud Dataplex is a data fabric that allows organizations to centrally manage, monitor and govern data across data lakes and data warehouses. It provides access to trusted data, while enabling analytics and AI to be powered at scale. Dataplex provides a unified data management interface that allows users to automate data discovery and classification, as well as metadata enrichment, for structured, semistructured, or unstructured data in Google Cloud, and beyond. It simplifies data curation, tiering and archiving by facilitating the logical organization into business-specific domains, using lakes and zones. Centralized governance and security features allow for policy management, monitoring and auditing across silos of data, allowing distributed data ownership and global oversight. Dataplex also has built-in capabilities for data quality and data lineage, automating data assessments and capturing lineage.

DataHub is a free and open-source metadata platform that streamlines data discovery, observability and governance across diverse data ecologies. It allows organizations to discover trustworthy data with experiences tailored to each user and eliminates breaking updates with detailed cross-platform, column-level lineage. DataHub gives you a complete view of your data, including its business, operational and technical context. The platform provides automated data quality checks, AI-driven anomaly identification and alerts teams when problems arise. It also centralizes incident tracking. DataHub's detailed ownership, documentation, and lineage information allows for quick issue resolution. It automates governance by classifying assets in real-time, reducing manual work with GenAI documentation, AI classification, and smart propagation. DataHub’s extensible architecture supports more than 70 native integrations.

5X is a data platform that offers everything you need to centralize your data, clean it, model it, and analyze it. 5X is designed to simplify data management. It offers seamless integration with more than 500 data sources. This ensures uninterrupted data movement between all your systems using pre-built connectors and custom connectors. The platform includes ingestion, warehousing and modeling, orchestration and business intelligence. All of this is presented in a simple-to-use interface. 5X supports a variety of data movements including SaaS applications, databases, ERPs and files. Data is transferred automatically and securely to data lakes and warehouses. 5X's enterprise-grade security encrypts the data at its source, identifying personally identifiable data and encrypting it at a column-level. The platform is designed for a 30% reduction in total cost of ownership compared to building a platform yourself. It also enhances productivity by providing a single interface for building end-to-end pipelines.

Connect and centralize data. Transform your data landscape into a flexible powerhouse. Data Virtuality is a data integration platform that allows for instant data access, data centralization, and data governance. Logical Data Warehouse combines materialization and virtualization to provide the best performance. For high data quality, governance, and speed-to-market, create your single source data truth by adding a virtual layer to your existing data environment. Hosted on-premises or in the cloud. Data Virtuality offers three modules: Pipes Professional, Pipes Professional, or Logical Data Warehouse. You can cut down on development time up to 80% Access any data in seconds and automate data workflows with SQL. Rapid BI Prototyping allows for a significantly faster time to market. Data quality is essential for consistent, accurate, and complete data. Metadata repositories can be used to improve master data management.

Alooma allows data teams visibility and control. It connects data from all your data silos into BigQuery in real-time. You can set up and flow data in minutes. Or, you can customize, enrich, or transform data before it hits the data warehouse. Never lose an event. Alooma's safety nets make it easy to handle errors without affecting your pipeline. Alooma infrastructure can handle any number of data sources, low or high volume.

Learn how users interact with your product and identify opportunities to help you make product decisions. Mode allows one Stitch analyst to perform the work of a full-time data team with speed, flexibility, collaboration. Create dashboards for annual revenue and then use chart visualizations quickly to identify anomalies. Share analysis with teams to create polished reports that are investor-ready. Connect your entire tech stack with Mode to identify upstream issues and improve performance. With webhooks and APIs, you can speed up team workflows. Learn how users interact with your product and identify areas for improvement. Use marketing and product data to identify weak points in your funnel, improve landing page performance, and prevent churn from happening.

The Databricks Data Intelligence Platform enables your entire organization to utilize data and AI. It is built on a lakehouse that provides an open, unified platform for all data and governance. It's powered by a Data Intelligence Engine, which understands the uniqueness in your data. Data and AI companies will win in every industry. Databricks can help you achieve your data and AI goals faster and easier. Databricks combines the benefits of a lakehouse with generative AI to power a Data Intelligence Engine which understands the unique semantics in your data. The Databricks Platform can then optimize performance and manage infrastructure according to the unique needs of your business. The Data Intelligence Engine speaks your organization's native language, making it easy to search for and discover new data. It is just like asking a colleague a question.