Development Status & Topics of Alinous Elastic DB

The development of this software is on going. This blog category shows what is going on, now.

Implement DELETE SQL Statement

This page is about internal implementation procedure of DELETE SQL statement in both Local & Remote SQL Mode.

On Transaction Engine

On transaction phase, from executing BEGIN to before COMMIT or ROLLBACK statement, the transaction engine uses record cache.

About record cache engine, please take a look at Execute Transaction Concurrently with Record Cache.

Scan Records to Delete

The DELETE statement has WHERE clause. It scans records which satisfy the condition in it. After that, it adds the records to deleted cache.

DML Lock on Scan

The transaction engine locks records on scanning. This lock is same with of UPDATE SQL statement.

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Created time: 2017-02-15 Last updated time: 2017-02-15

Execute Transaction Concurrently with Record Cache

Record Cache Engine

Concurrency Control of Transaction is implemented by records cache. This page explains how the cache is used.

Record Caches for Each Transaction

Record Caches are used to check which records are updated by local transaction.

Fast Concurrency Control

Alinous Elastic DB does not update data in the storage engine before committing the transaction.

Even if table partitioning or replication cluster is used, the data in the storage is single point on update it.

Read "Execute Transaction Concurrently with Record Cache" more


Created time: 2017-02-15 Last updated time: 2017-02-15

Implement UPDATE SQL Statement

This page is about internal implementation procedure of UPDATE SQL statement in both Local & Remote SQL Mode.

On Transaction Engine

On transaction phase, from executing BEGIN to before COMMIT or ROLLBACK statement, the transaction engine uses record cache.

On executing UPDATE statement, READ COMMITTED isolation level uses locks, but SERIALIZABLE level does not use locks.

About record cache engine, please take a look at Execute Transaction Concurrently with Record Cache.

Scan Records to Update

The UPDATE statement has WHERE clause. It scans records which satisfy the condition in it. After that, it makes cache records.

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Created time: 2017-02-15 Last updated time: 2017-02-15

Implement INERT SQL Statement

This page is about internal implementation procedure of INSERT SQL statement in both Local & Remote SQL Mode.

On Transaction Engine

On transaction phase, from executing BEGIN to before COMMIT or ROLLBACK statement, the transaction engine uses record cache.

The cache is used to store the updates of records. It is available from the transaction.

About record cache engine, please take a look at Execute Transaction Concurrently with Record Cache.

INSERT into Record Cache

The records in the INSERT statement is added to the cache. No locks are necessary, that is because it is transactionally independent.

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Created time: 2017-02-15 Last updated time: 2017-02-15

Implement from Local SQL Mode

Today is 14th February 2014. I'm going to implement Alinous Elastic DB from local mode, before remote mode, because it contains base of whole database architecture.

Distributed Database with Local Mode

Alinous Elastic DB has 2 execution modes, they are local mode and remote mode. It is not only scalable distributed database, but also high response database.

Local Mode

In local mode, database works on only local host. It works very fast in this mode, but not scalable. In addition to that, the database becomes portable.

Therefore, in following cases local mode is used.

  • On Debug and Development with Eclipse IDE
  • When high speed response, not scalability,  is necessary

Remote Mode

Remote mode is main mode to run on cloud server. In this mode, the database is scalable, with dynamic partitioning.

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Created time: 2017-02-14 Last updated time: 2017-02-14

NewSQL for OLTP & Bigdata

NewSQL is database management system which have more functions than RDBMS. It has distributed data management functions, that NoSQL is good at. Alinous Elastic DB is a kind of NewSQL.

Use Case of Bigdata

BigData is not simply huge data. That is high resolution data.

Data Acquisition Changes

Recently, IoT (Internet of Things) is a trending keyword. The IoT products generates a lot of data.

That is because the way to acquire data is changed by it. It takes a lot of detailed information as huge logs. As time passed, the data become bigger and bigger.

Detail Information for the Customer

When we acquire detail information about each customer, quantity of data become huge. In addition to that, it increases every day.

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Created time: 2017-02-11 Last updated time: 2017-02-11

NoSQL vs Distributed Relational Database

NoSQL is to solve problem of non-distributed database. But by adding distributed functions, RDBMS(Relational Database Management System) can do same things.

Advantage of NoSQL

NoSQL databases are basically very simple. But recently, they have some great functions about distributed data management.

The advantage of NoSQL is weak points of RDBMS.

Small Overhead

NoSQL for BigData, ex Hadoop, do not supports UPDATE and DELETE operation in SQL. In addition to no transaction support, it makes the structure simple.

Therefore it has almost no over head of Relational Databases.

Read "NoSQL vs Distributed Relational Database" more


Created time: 2017-02-11 Last updated time: 2017-02-11

Implicit Row Lock and Parallel Transaction Commit

Distributed Relational Database Management Systems can commit transactions as parallel process. In order to implement that, implicit row lock is necessary.

Implicit Locks on Transaction Execution

When we start a transaction, and executing UPDATE, DELETE, and INSERT SQL Statements, they implicitly lock database objects.

UPDATE and DELETE SQL Statement

Implicit row lock is done on executing UPDATE, DELETE Statement, after started a transaction before end of it.

Both SQL Statements has WHERE clause in it. It requests scanning to storage engines. Then update lock is done for filtered rows.

After getting result from storage engines, the transaction engine filters the result, again. Then filtered row's lock is released.

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Created time: 2017-02-09 Last updated time: 2017-02-09

How to Reduce Network Transfer between Storage & SQL Engine

Distributed Database is to handle big data with some remote networks nodes, so how to reduce network data is necessary issue.

Especially using database for OLTP use, it is essential to reduce it.

Distributed Database Engine & Storage Engine

The distributed database has storage engine architecture. Alinous Elastic DB has following one.

Reduce network transfer of Bigdata

The storage engine is accessed by SQL table access coordinator, which is called Region Manager in this database. It request scanning table to the storage engine, then it returns the result.

Read "How to Reduce Network Transfer between Storage & SQL Engine" more


Created time: 2017-02-07 Last updated time: 2017-02-07

Hot Replication among Remote Table Partition Nodes

When we update key's value of table partition on Remote Storage Node, it starts data transfer to the next remote node. Then the database does not stop, and it can process SQL statements.

In this article, I mention how to replicate and delete old data without stop.

Architecture of Storage Engine

This database is designed for dynamic table partitioning.

It has Storage Records Data Format and Distributed Storage Engine Architecture suitable for online data management.

Replication & Synchronizing Process on Table Partitioning

When rebuilding table partitions, it transfer data for next partitioning structure. Then it does not have to stop or lock the database.

Read "Hot Replication among Remote Table Partition Nodes" more


Created time: 2017-02-07 Last updated time: 2017-02-07
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