Best Big Data Software for Tabular

ANSI SQL allows you to analyze petabytes worth of data at lightning-fast speeds with no operational overhead. Analytics at scale with 26%-34% less three-year TCO than cloud-based data warehouse alternatives. You can unleash your insights with a trusted platform that is more secure and scales with you. Multi-cloud analytics solutions that allow you to gain insights from all types of data. You can query streaming data in real-time and get the most current information about all your business processes. Machine learning is built-in and allows you to predict business outcomes quickly without having to move data. With just a few clicks, you can securely access and share the analytical insights within your organization. Easy creation of stunning dashboards and reports using popular business intelligence tools right out of the box. BigQuery's strong security, governance, and reliability controls ensure high availability and a 99.9% uptime SLA. Encrypt your data by default and with customer-managed encryption keys

Secure and manage the data lifecycle, from Edge to AI in any cloud or data centre. Operates on all major public clouds as well as the private cloud with a public experience everywhere. Integrates data management and analytics experiences across the entire data lifecycle. All environments are covered by security, compliance, migration, metadata management. Open source, extensible, and open to multiple data stores. Self-service analytics that is faster, safer, and easier to use. Self-service access to multi-function, integrated analytics on centrally managed business data. This allows for consistent experiences anywhere, whether it is in the cloud or hybrid. You can enjoy consistent data security, governance and lineage as well as deploying the cloud analytics services that business users need. This eliminates the need for shadow IT solutions.

Trino is an engine that runs at incredible speeds. Fast-distributed SQL engine for big data analytics. Helps you explore the data universe. Trino is an extremely parallel and distributed query-engine, which is built from scratch for efficient, low latency analytics. Trino is used by the largest organizations to query data lakes with exabytes of data and massive data warehouses. Supports a wide range of use cases including interactive ad-hoc analysis, large batch queries that take hours to complete, and high volume apps that execute sub-second queries. Trino is a ANSI SQL query engine that works with BI Tools such as R Tableau Power BI Superset and many others. You can natively search data in Hadoop S3, Cassandra MySQL and many other systems without having to use complex, slow and error-prone copying processes. Access data from multiple systems in a single query.

Iceberg is an efficient format for large analytical tables. Iceberg brings the simplicity and reliability of SQL tables to the world of big data. It also allows engines like Spark, Trino Flink Presto Hive Impala and Impala to work safely with the same tables at the same time. Iceberg supports SQL commands that are flexible to merge new data, update rows, and perform targeted deletions. Iceberg can eagerly write data files to improve read performance or it can use delete-deltas for faster updates. Iceberg automates the tedious, error-prone process of generating partition values for each row in a table. It also skips unnecessary files and partitions. There are no extra filters needed for fast queries and the table layout is easily updated when data or queries change.

Starburst allows you to make better decisions by having quick access to all of your data. Your company has more data than ever, but your data teams are still waiting to analyze it. Starburst gives your data teams quick and accurate access to more data. Starburst Enterprise, a fully supported, production-tested, enterprise-grade distribution for open source Trino (formerly Presto®, SQL), is now available. It increases performance and security, while making it easy for you to deploy, connect, manage, and manage your Trino environment. Starburst allows your team to connect to any source of data, whether it's on-premise, in a cloud, or across a hybrid cloud environment. This allows them to use the analytics tools they already love and access data that lives anywhere.

Apache Spark™, a unified analytics engine that can handle large-scale data processing, is available. Apache Spark delivers high performance for streaming and batch data. It uses a state of the art DAG scheduler, query optimizer, as well as a physical execution engine. Spark has over 80 high-level operators, making it easy to create parallel apps. You can also use it interactively via the Scala, Python and R SQL shells. Spark powers a number of libraries, including SQL and DataFrames and MLlib for machine-learning, GraphX and Spark Streaming. These libraries can be combined seamlessly in one application. Spark can run on Hadoop, Apache Mesos and Kubernetes. It can also be used standalone or in the cloud. It can access a variety of data sources. Spark can be run in standalone cluster mode on EC2, Hadoop YARN and Mesos. Access data in HDFS and Alluxio.

Azure Databricks allows you to unlock insights from all your data, build artificial intelligence (AI), solutions, and autoscale your Apache Spark™. You can also collaborate on shared projects with other people in an interactive workspace. Azure Databricks supports Python and Scala, R and Java, as well data science frameworks such as TensorFlow, PyTorch and scikit-learn. Azure Databricks offers the latest version of Apache Spark and allows seamless integration with open-source libraries. You can quickly spin up clusters and build in an Apache Spark environment that is fully managed and available worldwide. Clusters can be set up, configured, fine-tuned, and monitored to ensure performance and reliability. To reduce total cost of ownership (TCO), take advantage of autoscaling or auto-termination.