Best Data Management Software for Alibaba Cloud

Splunk is a secure, reliable, and scalable service that turns data into answers. Our Splunk experts will manage your IT backend so you can concentrate on your data. Splunk's cloud-based data analytics platform is fully managed and provisioned by Splunk. In as little as two days, you can go live. Software upgrades can be managed to ensure that you have the most recent functionality. With fewer requirements, you can tap into the data's value in days. Splunk Cloud is compliant with FedRAMP security standards and assists U.S. federal agencies, their partners, and them in making confident decisions and taking decisive actions at rapid speed. Splunk's mobile apps and augmented reality, as well as natural language capabilities, can help you increase productivity and contextual insight. Splunk solutions can be extended to any location by simply typing a phrase or tapping a finger. Splunk Cloud is designed to scale, from infrastructure management to data compliance.

Our unified cloud solution for data and analytics enables business users to connect data with business contexts and unlock insights. SAP Data Warehouse Cloud unites data and analytics in a cloud platform that includes data integration, data warehouse, data warehouse, as well as analytics capabilities. This will help you unleash your data-driven enterprise. Built on the SAP HANA Cloud database, this software-as-a-service (SaaS) empowers you to better understand your business data and make confident decisions based on real-time information. You can connect data across multi-cloud and local repositories in real time, while keeping the context of your business. SAP HANA Cloud enables you to gain insights and analyze real-time data at lightning speed. All users can access self-service capabilities to connect, model and visualize their data securely in an IT-governed environment. Use pre-built templates, data models, and industry content.

Data intelligence can transform data chaos into data value. Disjointed data assets can be connected, discovered, enriched, and orchestrated to provide actionable business insights at an enterprise scale. SAP Data Intelligence provides a comprehensive data management solution. It is the data orchestration layer within SAP's Business Technology Platform. It transforms distributed data into vital data insights and delivers innovation at scale. Integrate across the IT landscape to provide intelligent, relevant and contextual insights for your users. Integrate and orchestrate large data volumes and streams at scale. Machine learning enables you to streamline, operationalize, manage, and govern innovation. Comprehensive metadata management rules optimize governance and reduce compliance risk. Disjointed data assets can be connected, discovered, enriched, and orchestrated to provide actionable business insights at enterprise level.

Tableau Catalog is a benefit for everyone. Tableau Catalog provides a complete view of the data and how it connects to the analytics in Tableau. This increases trust and discoverability for IT and business users. Tableau Catalog makes it easy to communicate changes to the data, review dashboards, or search for the right data for analysis. Tableau Catalog automatically ingests all data assets in your Tableau environment into a single central list. There is no need to create an index schedule or connect. You can quickly see all of your files, tables, and databases in one location. Migration of databases, deprecating fields or adding a column to a table can all have potential impacts on your environment. Lineage and impact analysis allows you to see not only the upstream and downstream implications of assets but also who will be affected.

Navicat Data Modeller is a powerful, cost-effective database design tool that helps you create high-quality conceptual and logical data models. It can be used to create database structures, reverse/forward engineer processes, import models directly from ODBC data sources, create complex SQL/DDL, and print models to files. It makes it easy to create complex entity relationship models. You can also generate script SQL in just one click. Navicat Data Modeler supports many database systems including MySQL, MariaDB and Oracle, SQL Servers, PostgreSQL and SQLite. Professional object designers are available for Tables or Views. They can help you create, modify, and design models. You'll always know what you are doing, even if you don't need to write complex SQL. Navicat Data Modeler also supports three standard notations: Crow's Foot (IDEF1x), UML (Unified Modeling Language) and UML.

PolarDB-X was tested at the Tmall Double 11 shopping festival. It has helped customers in a variety of industries, including finance, logistics, energy and public service, to address business problems. Linearly increases storage space to provide petabyte scale storage. This eliminates storage bottlenecks in standalone databases. Massively parallel processing (MPP), which allows for complex analysis and queries on large amounts of data to be significantly improved. It provides extensive algorithms to distribute data across multiple storage devices, effectively reducing the amount of data stored in one table.

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.

SelectDB is an advanced data warehouse built on Apache Doris. It supports rapid query analysis of large-scale, real-time data. Clickhouse to Apache Doris to separate the lake warehouse, and upgrade the lake storage. Fast-hand OLAP system carries out nearly 1 billion queries every day in order to provide data services for various scenes. The original lake warehouse separation was abandoned due to problems with storage redundancy and resource seizure. Also, it was difficult to query and adjust. It was decided to use Apache Doris lakewarehouse, along with Doris's materialized views rewriting capability and automated services to achieve high-performance query and flexible governance. Write real-time data within seconds and synchronize data from databases and streams. Data storage engine with real-time update and addition, as well as real-time polymerization.

Astronomer is the driving force behind Apache Airflow, the de facto standard for expressing data flows as code. Airflow is downloaded more than 4 million times each month and is used by hundreds of thousands of teams around the world. For data teams looking to increase the availability of trusted data, Astronomer provides Astro, the modern data orchestration platform, powered by Airflow. Astro enables data engineers, data scientists, and data analysts to build, run, and observe pipelines-as-code. Founded in 2018, Astronomer is a global remote-first company with hubs in Cincinnati, New York, San Francisco, and San Jose. Customers in more than 35 countries trust Astronomer as their partner for data orchestration.

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.

EMR is an enterprise-ready big-data platform that offers cluster, job, data management and other services. It is based on open-source ecosystems such as Hadoop Spark, Kafka and Flink. Alibaba Cloud Elastic MapReduce is a big-data processing solution that runs on the Alibaba Cloud platform. EMR is built on Alibaba Cloud ECS and is based open-source Apache Spark and Apache Hadoop. EMR allows you use the Hadoop/Spark ecosystem components such as Apache Hive and Apache Kafka, Flink and Druid to analyze and process data. EMR can be used to process data stored on different Alibaba Cloud data storage services, such as Log Service (SLS), Object Storage Service(OSS), and Relational Data Service (RDS). It is easy to create clusters quickly without having to install hardware or software. Its Web interface allows you to perform all maintenance operations.

With exceptional functionality for data integration, quality and cleansing, maximize the value of all structured and unstructured data in your organization. SAP Data Services software increases the quality of enterprise data. It is part of SAP's Information Management Layer. It delivers timely, relevant, and trusted information to help drive better business outcomes. Transform your data into a reliable, always-available resource for business insights and use it to streamline operations and maximize efficiency. Get contextual insight and unlock the true potential of your data with a complete view of all your information. Access to any size data and any source. Standardizing and matching data can improve decision-making and operational efficiency. This will reduce duplicates, identify relationships and address quality issues proactively. Use intuitive tools to unify critical data whether it is on-premise, in the cloud or within Big Data.

Transform your applications to ensure local compliance and security. While still using the cloud, map your controls and improve compliance programs. Your custom apps can be made to comply with data residency requirements without any additional development. You can enter new markets and increase revenue without affecting your customers' experience. InCountry ensures that your financial services applications are compliant with data regulations in more nations, so you can get the most out of them. A modern data compliance platform will help you protect your path to precision medicine. InCountry offers healthcare-focused solutions that can accelerate research and time to discovery. You can enter new markets and increase revenue without affecting your customer experience. InCountry ensures that your sales process is compliant with local data regulations.

Hadoop has been an integral part of the data management landscape since 2010. The majority of organizations that have adopted Hadoop over the past decade to build their data lake infrastructure. Although Hadoop was a cost-effective method to store petabytes in a distributed environment, there were many complexities. The systems required IT skills that were specialized and the on-premises environments did not allow for the ability to scale up or down as the usage requirements changed. Cloud computing addresses the complexity and flexibility issues associated with Hadoop environments on-premises. Many companies have chosen to automate cloud data migration using WANdisco to reduce the risks and cost associated with modernizing their data. LiveData Migrator can be used as a self-service tool and does not require any WANdisco services or expertise.

MaxCompute, formerly known as ODPS, is a multi-tenant, general-purpose data processing platform that can be used for large-scale data warehousing. MaxCompute supports a variety of data importing options and distributed computing models. This allows users to query large datasets efficiently, reduce production costs, and ensure data safety. Supports EB-level data storage. Supports SQL, MapReduce and Graph computational models as well as Message Passing Interface (MPI), iterative algorithms. This cloud is more efficient than an enterprise private cloud and offers storage and computing services that are up to 20% to 30% cheaper. Stable offline analysis services that last more than seven years. Also, multi-level sandbox protection is possible. Monitoring and monitoring are possible. MaxCompute uses tunnels for data transmission. Tunnels can be scaled and used to import and export PB-level data daily. Multiple tunnels allow you to import all data and history data.

Alibaba Cloud launched DataWorks, a Big Data platform product. It offers Big Data development, data permission management and offline job scheduling. DataWorks is easy to use and does not require any special cluster setup or management. To create a workflow, drag and drop nodes. Online editing and debugging of code is possible. You can also ask other developers to join your project. Data integration, MaxCompute SQL and MaxCompute MS, machine learning, shell tasks, and MaxCompute MR are supported. To prevent service interruptions, task monitoring is supported. It sends alarms when errors are detected. It can run millions of tasks simultaneously and supports hourly, daily and weekly schedules. DataWorks is the best platform to build big data warehouses. It also offers comprehensive data warehousing and support services. DataWorks offers a complete solution for data aggregation and processing, as well as data governance and data services.

AnalyticDB for MySQL, a high-performance data warehouse service, is safe, stable, and simple to use. It makes it easy to create online statistical reports, multidimensional analyses solutions, and real time data warehouses. AnalyticDB for MySQL uses distributed computing architecture which allows it to use elastic scaling capabilities of the cloud to compute tens to billions of data records in real-time. AnalyticDB for MySQL stores data using relational models. It can also use SQL to compute and analyze data. AnalyticDB for MySQL allows you to manage your databases, scale in and out nodes, scale up or down instances, and more. It offers various visualization and ETL tools that make data processing in enterprises easier. Instant multidimensional analysis of large data sets.

The only fully-managed cloud data lakehouse that can ingest data from all of your sources in minutes, and support all of your query engines on a large scale. All for a fraction the cost. With the ease of fully managed pipelines, you can ingest data from databases and event streams in near-real-time. You can query your data using any engine and support all of your use cases, including BI, AI/ML, real-time analytics and AI/ML. Simple usage-based pricing allows you to cut your costs by up to 50% compared with cloud data warehouses and ETL software. With a fully-managed, highly optimized cloud service, you can deploy in minutes and without any engineering overhead. Unify all your data into a single source and eliminate the need for data to be copied between data lakes and warehouses. Apache Hudi, Apache Iceberg and Delta Lake all offer omnidirectional interoperability, allowing you to choose the best table format for your needs. Configure managed pipelines quickly for database CDC and stream ingestion.

You can accelerate hybrid cloud adoption, scale out as required, and manage data workloads all from one intuitive platform. A simple scale-out solution that integrates seamlessly with Commvault’s Intelligent Data Management platform. You can accelerate your digital transformation journey with unmatched security, scalability, and resilience. All workloads, including virtual and containers, are protected with simple, flexible data protection. Concurrent hardware failures are prevented from affecting data availability with built-in resilience. Data reuse is possible through copy data management, which provides instant recovery of VMs as well as live production copies for DevOps or testing. High-performance backup with recovery, enhanced RPO and reduced RTO. Cloud data mobility that is cost-optimized to move data between, within, and between clouds. Disaster recovery testing of replicas directly on the hardware.

A family of integrated solutions that provide actionable insights. It includes Commvault Data Governance and Commvault File Optimization. We are creating more data than ever before. It is important to know everything about it. Automated and proactive actions can be taken to speed up response times, prevent data theft or breaches, eliminate data sprawl, as well as make data-driven decisions in your organization. You can increase storage efficiency and enable faster responses to compliance inquiries. Your data risks are reduced with analytics, reporting and search across backup and production data sources. Advanced "4D" technology delivers a centralized, dynamic, multi-dimensional index of metadata and content, classifications, as well as AI applied insights. A single index that is consistent across all data sources, including remote, cloud, on-premises, and backup, gives you visibility into production and backup data. You can search, filter, drill down and create custom dashboards.

Alibaba Cloud's Distributed Relational Database Service is a lightweight, flexible and stable middleware product. DRDS focuses primarily on expanding standalone relational database and has been tested using core transaction links in Tmall such as during Singles' Day Shopping Festival. DRDS is trusted and has been in use for ten years. Cluster-based data read/write and data storage. DRDS works on multiple servers and is not affected by the number or quality of connections. Supports upgrading and downgrading data configurations and the visualization of scale-up/scale-out of data storage. To improve linearly the reading performance, read and write splitting is available. Multiple data splitting methods are available depending on the data type, such as parallel data split. Supports parallel query execution and focuses on the primary shards.

Delta Lake is an open-source storage platform that allows ACID transactions to Apache Spark™, and other big data workloads. Data lakes often have multiple data pipelines that read and write data simultaneously. This makes it difficult for data engineers to ensure data integrity due to the absence of transactions. Your data lakes will benefit from ACID transactions with Delta Lake. It offers serializability, which is the highest level of isolation. Learn more at Diving into Delta Lake - Unpacking the Transaction log. Even metadata can be considered "big data" in big data. Delta Lake treats metadata the same as data and uses Spark's distributed processing power for all its metadata. Delta Lake is able to handle large tables with billions upon billions of files and partitions at a petabyte scale. Delta Lake allows developers to access snapshots of data, allowing them to revert to earlier versions for audits, rollbacks, or to reproduce experiments.

Unstructured data is the future for AI. This future is now possible. Build an ML/AI pipeline to scale all your unstructured data from one place. Graviti allows you to use better data to create better models. Learn about Graviti, the data platform that allows AI developers to manage, query and version control unstructured data. Quality data is no longer an expensive dream. All your metadata, annotations, and predictions can be managed in one place. You can customize filters and see the results of filtering to find the data that meets your needs. Use a Git-like system to manage data versions and collaborate. Role-based access control allows for safe and flexible team collaboration. Graviti's built in marketplace and workflow creator makes it easy to automate your data pipeline. No more grinding, you can quickly scale up to rapid model iterations.

Hologres, a cloud-native Hybrid Serving & Analytical Processing system (HSAP), is seamlessly integrated into the big data ecosystem. Hologres can be used to process PB-scale data at high concurrency with low latency. Hologres allows you to use your business intelligence (BI), tools to analyze data in multiple dimensions. You can also explore your business in real time. Hologres eliminates data silos and redundancy that are disadvantages of traditional real time data warehousing systems. It can be used to migrate large amounts of data and perform real-time analysis. It responds to queries on PB scale data at sub-second speeds. This speed allows you to quickly analyze data in multiple dimensions and examine your business in real time. Supports concurrent writes and queries at speeds up to 100,000,000 transactions per second (TPS). Data can be accessed immediately after it has been written.

A data lake is a central repository for big data and AI computing. It allows you to store both structured and unstructured data at any size. Data Lake Formation (DLF), is a key component in the cloud-native database lake framework. DLF is a simple way to create a cloud-native database lake. It integrates seamlessly with a variety compute engines. You can manage metadata in data lakes in an centralized manner and control enterprise class permissions. It can systematically collect structured, semi-structured and unstructured data, and supports massive data storage. This architecture separates storage and computing. This allows you to plan resources on demand and at low costs. This increases data processing efficiency to meet rapidly changing business needs. DLF can automatically detect and collect metadata from multiple engines. It can also manage the metadata in a central manner to resolve data silo problems.