Feature
High Performance
Supports memory tables for ultra-fast transaction processing
High Availability
- Multi process architecture
- Replica Node Support
- Redo log and checkpoint background processing
Scalability
- Scale in/out for large-scale data distribution and processing
- Versatility
Versatility
- Use table modes suitable for tasks with Memory TBS and Disk TBS
- Flexible system configurations tailored to user requirements
High Performance
Goldilocks was developed as an In-Memory Architecture.
- Data is kept resident in memory, avoiding any Disk IO operations.
- Only algorithms optimized for in-memory operations are used.
- Logging for index changes is not required, leading to reduced logging IO costs.
- In-memory transactions similarly use the WAL (Write-Ahead Logging) algorithm to safeguard against data loss.
* Data is kept resident in memory,
avoiding any Disk IO operations.
* Only algorithms optimized
for in-memory operations are used.
* Logging for index changes is not required, leading to reduced logging IO costs.
* In-memory transactions similarly use
the WAL (Write-Ahead Logging) algorithm
to safeguard against data loss.
High Availability
Simple configuration of the application to support failover
Failover configuration (connection string)
ALTERNATE_SERVERS = (HOST=192.168.0.101:PORT=22581,
HOST=192.168.0.102:PORT=22581,
HOST=192.168.0.103:PORT=22581)
retry:
EXEC SQL UPDATE POC_DEDUCTIONSET USG_USED_AMOUNT =…
if( sqlca.sqlcode == DB_RETRY_TRANS )
{
goto tx_retry;
}
App error code configuration
GOLDILOCKS operates seamlessly in virtualization environments such as OpenStack and Kubernetes.
Achieve high availability with perfect support
for Active-Active configurations.
* Real-time data synchronization
* Active-Active configuration allows DDL/DML/SELECT operations on all members
* Application-level auto-failover features (CTF/STF) ensure uninterrupted service even in the event of node failures
Scalability
Users can select from various sharding policies
for distributed processing of large-scale data.
-
Data is distributed and stored according to
the sharding policy selected by the user. -
Data can be joined and global transactions can be
processed across cluster groups. -
Data from multiple nodes can be used as if it were a single database.
-
Supported sharding policies : Hash, Range, List, Cloned
Large-scale data distributed processing – Scale In/Out
* Ensure availability through a multiplexed configuration.
* Enhanced availability and performance with multiplexing and distributed processing.
범용성
Use the table mode best suited for your workload with Memory TBS and DISK TBS.
Various environment configurations
Goldilocks Cluster can be configured in various ways to meet user requirements.
* Active-Active
* Active-standby
* Multiplexing & distributed processing
Tools
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