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OceanBase

A unified distributed database ready for your transactional, analytical, and AI workloads.

Product Overview
DEPLOY YOUR WAY

OceanBase Cloud

The best way to deploy and scale OceanBase

OceanBase Enterprise

Run and manage OceanBase on your infra

TRY OPEN SOURCE

OceanBase Community Edition

The free, open-source distributed database

OceanBase seekdb

Open source AI native search database

Customer Stories

Real-world success stories from enterprises across diverse industries.

View All
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Mission-Critical Transactions

Global & Multicloud Application

Elastic Scaling for Peak Traffic

Real-time Analytics

Active Geo-redundancy

Database Consolidation

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    MemTables

    Last Updated:2026-04-15 08:25:14  Updated
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    Data structure in a MemTable
    Characteristics of the two data structures

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    Data structure in a MemTable

    The memory storage engine (MemTable) of OceanBase Database consists of B-trees and hash tables. When data is inserted, updated, or deleted, the data is written into the memory block. Hash tables and B-trees store the pointers to the corresponding data.

    memtable-structure.png

    Characteristics of the two data structures

    Data structure
    Advantage
    Disadvantage
    Hash table Before OceanBase Database inserts a row of data, it checks whether this row of data already exists. OceanBase Database inserts the data only when it does not exist. Data checks for hash tables are faster than those for B-trees. When a transaction inserts or updates a row of data, it needs to find this row and lock it to prevent other transactions from modifying the row. Row locks in OceanBase Database are stored in the row header data structure. The transaction must find a row lock before it locks the row. Hash tables are not suitable for range queries.
    B-tree Data in B-trees is ordered. This design allows OceanBase Database to search for only local data when it performs range queries. Single-row queries require the comparison of a large number of primary keys from the root node to the leaf nodes. However, it is relatively difficult to compare primary keys in B-trees. In theory, the query speed in B-tree is much slower than that in hash tables.

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