Compare the Top OLAP Databases in China as of November 2025

What are OLAP Databases in China?

OLAP (Online Analytical Processing) databases are designed to support complex queries and data analysis, typically for business intelligence and decision-making purposes. They enable users to interactively explore large volumes of multidimensional data, offering fast retrieval of insights across various dimensions such as time, geography, and product categories. OLAP databases use specialized structures like cubes to allow for rapid aggregation and calculation of data. These databases are highly optimized for read-heavy operations, making them ideal for generating reports, dashboards, and analytical queries. Overall, OLAP databases help organizations quickly analyze data to uncover patterns, trends, and insights for better decision-making. Compare and read user reviews of the best OLAP Databases in China currently available using the table below. This list is updated regularly.

  • 1
    Teradata VantageCloud
    Teradata VantageCloud is a cloud-native OLAP database platform designed for complex, high-performance analytical workloads at enterprise scale. It enables multidimensional analysis across structured and semi-structured data, supporting advanced SQL queries, real-time analytics, and AI/ML integration. VantageCloud runs across multi-cloud and hybrid environments, offering elastic scalability and robust workload management. Its open architecture ensures compatibility with modern data tools and formats, while built-in governance and security features support trusted, compliant analytics. Ideal for organizations needing fast, reliable insights from large, diverse datasets.
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  • 2
    icCube

    icCube

    icCube

    icCube is a Swiss embeddable analytics solution designed for B2B SaaS product and development teams to deeply embed analytic capabilities inside their applications. Dashboards will seamlessly blend into the SaaS solution’s UI and UX experience, while resting on top of icCube’s robust analytical engine, allowing to consume complex data models needing sophisticated data security. With a dev2dev approach, icCube's team accompanies clients to successfully and quickly get into production. At icCube, we understand that navigating the complexities of data can be daunting. That’s why we’re excited to introduce also our Data Analytics Boutique Services, designed to empower both existing and new clients in achieving seamless data integration, robust data security, insightful analytics, effective decision automation and dashing reports. We partner with our clients at all stages and all phases of their projects and product roadmaps. From a quick review up to a full project and product
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    Starting Price: $20,000/year
  • 3
    ScyllaDB

    ScyllaDB

    ScyllaDB

    ScyllaDB is the database for data-intensive apps that require high performance and low latency. It enables teams to harness the ever-increasing computing power of modern infrastructures – eliminating barriers to scale as data grows. Unlike any other database, ScyllaDB is a distributed NoSQL database fully compatible with Apache Cassandra and Amazon DynamoDB, yet is built with deep architectural advancements that enable exceptional end-user experiences at radically lower costs. Over 400 game-changing companies like Disney+ Hotstar, Expedia, FireEye, Discord, Zillow, Starbucks, Comcast, and Samsung use ScyllaDB for their toughest database challenges. ScyllaDB is available as free open source software, a fully-supported enterprise product, and a fully managed database-as-a-service (DBaaS) on multiple cloud providers.
  • 4
    Apache Druid
    Apache Druid is an open source distributed data store. Druid’s core design combines ideas from data warehouses, timeseries databases, and search systems to create a high performance real-time analytics database for a broad range of use cases. Druid merges key characteristics of each of the 3 systems into its ingestion layer, storage format, querying layer, and core architecture. Druid stores and compresses each column individually, and only needs to read the ones needed for a particular query, which supports fast scans, rankings, and groupBys. Druid creates inverted indexes for string values for fast search and filter. Out-of-the-box connectors for Apache Kafka, HDFS, AWS S3, stream processors, and more. Druid intelligently partitions data based on time and time-based queries are significantly faster than traditional databases. Scale up or down by just adding or removing servers, and Druid automatically rebalances. Fault-tolerant architecture routes around server failures.
  • 5
    Databricks Data Intelligence Platform
    The Databricks Data Intelligence Platform allows your entire organization to use data and AI. It’s built on a lakehouse to provide an open, unified foundation for all data and governance, and is powered by a Data Intelligence Engine that understands the uniqueness of your data. The winners in every industry will be data and AI companies. From ETL to data warehousing to generative AI, Databricks helps you simplify and accelerate your data and AI goals. Databricks combines generative AI with the unification benefits of a lakehouse to power a Data Intelligence Engine that understands the unique semantics of your data. This allows the Databricks Platform to automatically optimize performance and manage infrastructure in ways unique to your business. The Data Intelligence Engine understands your organization’s language, so search and discovery of new data is as easy as asking a question like you would to a coworker.
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    DuckDB

    DuckDB

    DuckDB

    Processing and storing tabular datasets, e.g. from CSV or Parquet files. Large result set transfer to client. Large client/server installations for centralized enterprise data warehousing. Writing to a single database from multiple concurrent processes. DuckDB is a relational database management system (RDBMS). That means it is a system for managing data stored in relations. A relation is essentially a mathematical term for a table. Each table is a named collection of rows. Each row of a given table has the same set of named columns, and each column is of a specific data type. Tables themselves are stored inside schemas, and a collection of schemas constitutes the entire database that you can access.
  • 7
    BigObject

    BigObject

    BigObject

    At the heart of our innovation is in-data computing, a technology designed to process large amounts of data efficiently. Our flagship product, BigObject, embodies this core technology; it’s a time series database developed with the goal of high-speed storage and handling of massive data. With our core technology of in-data computing, we launched BigObject, which can quickly and continuously handle non-stop and all aspects of data streams. BigObject is a time series database developed with the goal of high-speed storage and analysis of massive data. It boasts excellent performance and powerful complex query capabilities. Extending the relational data structure to a time-series model structure, it utilizes in-data computing to optimize the database’s performance. Our core technology is an abstract model in which all data is kept in an infinite and persistent memory space for both storage and computing.
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