TiDB · TiKV · TiFlash · PDTiDB, scaled out, never sharded by hand.
TiDB is an open-source distributed SQL database combining ACID transactional processing (OLTP) and real-time analytics (OLAP) into a single Hybrid Transactional/Analytical Processing (HTAP) architecture. JusDB delivers end-to-end TiDB reliability engineering, TiKV Raft tuning, TiFlash MPP query optimization, and low-downtime MySQL migrations, with agreed incident response (24x7 on-call available).
Scalable, high-performance, and cloud-native HTAP database solution. Combine transactional and analytical processing in a single platform with horizontal scaling capabilities.
TiDB 7.5 · distributed SQL
PD + TiKV + TiFlash · Raft
4.82k
18.4k
6ms
100%
Cluster Throughput
4.82k QPS[OK] pd: scheduling balanced, 0 pending operators
[INF] tikv: region 4471 split — hot key relieved
[OK] tiflash: replica sync 100%, HTAP ready
[INF] raft: leader election complete, store-3 → leader
Example monitoring view showing database activity and engineer actions. Uses sample data, not customer data.
24
Supported database technologies
24x7
On-call coverage, under your service agreement
30 min
P1 initial-response target on 24x7 on-call
2 to 4 h
Initial-response target in covered business hours
TiDB engineering
Complete TiDB lifecycle support: architecture, optimization, migrations, and operations from distributed SQL specialists.
HTAP Architecture Design
Design and deploy TiDB clusters capable of parallel processing high-volume OLTP traffic alongside intensive OLAP real-time analytics.
TiKV & TiFlash Optimization
Optimize row-based TiKV storage engines for transactions and columnar TiFlash nodes for sub-second analytical queries.
Low-Downtime Migrations
Execute seamless migrations from MySQL/Aurora using TiDB Data Migration (DM) for full load plus live incremental binlog replication.
Query & Planner Tuning
Tune the TiDB cost-based optimizer (CBO) and utilize SQL execution plan management (SPM) for predictable performance.
Auto-Sharding & Scaling
Configure horizontal scaling to eliminate MySQL sharding limitations and handle massive data growth without application changes.
Disaster Recovery & Backup
Implement physical backup architectures using BR (Backup & Restore) tool for high-speed snapshot/log restorations.
TiDB expertise
Our distributed SQL engineers unlock true HTAP performance with tailored configurations across TiKV and TiFlash engines.
Distributed SQL Performance
After tuningIllustrative health scores · results depend on the workload
Workloads we've transformed
Illustrative examples of the problem and the fix, not client measurements.
820ms
9ms
Sequential write hotspot on one TiKV region
The fix
PD split + scatter hot region; SHARD_ROW_ID_BITS=4
45s
1.2s
Analytical aggregate hammering OLTP row store
The fix
ALTER TABLE orders SET TIFLASH REPLICA 2 — MPP engine
9,400ms
120ms
Full scan pulling 12M rows to TiDB layer
The fix
Pushed filter + agg into TiKV coprocessor, 2% rows return
4/4
Components online
<10s
Failover RTO
0ms
Replica Lag
Always on. Raft-powered.
Multi-region Raft consensus, automatic leader re-election, and cross-datacenter disaster recovery — validated with failover drills, with no manual failover intervention. Availability targets are agreed per workload and written into your service agreement.
A region-split P1, answered within your agreement's target.
When a network partition triggers Raft re-election or region imbalance stalls queries, a named TiDB engineer responds — not a ticket queue. Root-cause diagnosis and PD schedule tuning applied online.
TiKV store p99 above 800ms; one hot region overloaded
A named TiDB engineer responds within your agreement's initial-response target
Sequential write hotspot: one region absorbing all traffic
Split and scattered the hot region; SHARD_ROW_ID_BITS set on the table
Load spread across stores and p99 back to baseline; post-incident review
TiDB Engine Internals: Critical Failure Modes
Scaling distributed SQL requires continuous oversight of consensus storage and execution plan isolation. Here are the 3 engine failure modes our TiDB SRE team permanently remediates:
Region Hotspotting & Monotonic Key Write Contention
Sequential auto-increment primary keys cause all insert traffic to hit a single TiKV Region (the tail region) and a single Raft Leader, causing severe CPU and disk I/O bottlenecks while remaining cluster nodes sit idle.
Designing clustered index schemas using SHARD_ROW_ID_BITS and PRE_SPLIT_REGIONS, or adopting AUTO_RANDOM primary keys to evenly scatter writes across the entire TiKV fleet.
TiFlash MPP Query Plan Fallback & Network Shuffle Saturation
Analytical queries intended for columnar TiFlash execution fall back to row-based TiKV scans due to cost-based optimizer (CBO) statistical skew or unsupported window functions, saturating the cluster network fabric with unvectorized data transfers.
Calibrating tidb_isolation_read_engines = 'tidb,tiflash', tuning dynamic histogram statistics via ANALYZE TABLE, and enforcing SQL Execution Plan Management (SPM) baselines.
Placement Driver (PD) Raft Heartbeat Overhead & Region Fragmentation
An explosion of millions of small or empty TiKV Regions increases Raft heartbeat traffic and memory overhead on the PD leader, slowing down region scheduling, transaction timestamp allocation (TSO), and cluster rebalancing.
Configuring automated Region merge rules (merge-schedule-limit, max-merge-region-size 96MB), tuning PD leader lease timeouts, and cleaning up unneeded small partitions.
Our TiDB SREs execute read-only information_schema queries to identify write hotspotting and coprocessor query delays without impacting active transactions:
SELECT region_id,
peer_id,
store_id,
is_leader,
written_bytes,
read_bytes,
flow_type
FROM information_schema.tidb_hot_regions
ORDER BY written_bytes DESC
LIMIT 10;SELECT time,
query_time,
wait_time,
cop_proc_avg,
mem,
query
FROM information_schema.cluster_slow_query
WHERE time > now() - INTERVAL 1 HOUR
ORDER BY query_time DESC
LIMIT 5;How JusDB TiDB Services compare to alternative options.
Deploying TiDB for mission-critical HTAP eliminates MySQL sharding, but demands precision management of TiKV Raft consensus, TiFlash MPP execution, and Placement Driver scheduling. Here is how JusDB compares to managed cloud tiers, generic MSPs, and internal teams.
| Engineering Dimension | JusDB TiDB SRE | TiDB Cloud Managed | Generic MSPs | In-House Devs |
|---|---|---|---|---|
| Distributed Region Key Partitioning & Hotspot Elimination | SHARD_ROW_ID_BITS, PRE_SPLIT_REGIONS, and AUTO_RANDOM key distribution preventing monotonic write bottlenecks | Dashboard exposes hotspot graphs; customer is responsible for redesigning DDL schemas and partition logic | Treats TiDB as standard MySQL; unaware of distributed Region key ranges and Raft leader write hotspots | Sequential auto-increment IDs route 100% of write traffic to a single TiKV node, crushing ingestion throughput |
| HTAP Isolation: TiKV OLTP vs TiFlash MPP OLAP | Strict read-engine isolation (tidb_isolation_read_engines), SPM plan baselines, and TiFlash replica replication lag monitoring | TiFlash node creation available in UI; no automated protection against analytical queries spilling into TiKV row engines | Does not configure TiFlash columnar storage; analytical queries cause lock and CPU contention on transactional nodes | Heavy reporting queries run against TiKV row engine, causing p99 transaction latencies to spike into multi-seconds |
| Placement Driver (PD) Scheduling & Region Health | Automated empty-region merging, PD leader TSO latency optimization, and cross-datacenter placement rules | Standard PD scheduling presets; region fragmentation accumulates over time on high-drop tables | Lacks understanding of PD Raft state machine and consensus scheduling internals | Millions of unmerged 1MB regions overload PD memory, degrading cluster-wide metadata operations |
| Incident Response & Escalation | Direct Slack/Teams incident bridge to named TiDB engineers. Initial-response targets: 2 to 4 hours in covered business hours; 30 minutes for P1 incidents with 24x7 on-call. Targets, not resolution guarantees. | Multi-tiered support queue; requires enterprise tier for 1-hour P1 response with generic cloud engineers | Offshore ticket dispatcher with no training in distributed consensus protocols or TiKV storage engines | Engineers struggling to debug complex distributed execution plan anomalies during production outages |
| MySQL Compatibility & Low-Downtime Live Migration | TiDB Data Migration (DM) pipelines with incremental binlog replication, schema compatibility audits, and a short, rehearsed cutover | Basic import utilities available, but requires manual configuration of DM workers and filter rules | Attempts logical dump and restore with mysqldump, resulting in multi-hour maintenance downtime windows | Migration stalled by unsupported MySQL features (stored procedures, foreign keys) without automated workarounds |
| Backup, Point-In-Time Recovery (PITR) & FinOps | Physical distributed backups via BR (Backup & Restore), S3/GCS immutable snapshots, and continuous log backup verification | Cloud snapshots provided with steep backup storage retention fees and limited restore granularity | Relies on standard file-level or VM backups that cannot guarantee distributed transactional consistency | Unverified backups that fail recovery drills due to mismatched Raft log snapshots across TiKV nodes |
Pre-Migration Assessment
MySQL → TiDB · DM + TiCDC
Near-zero-downtime cutover window: < 5 minutes
Move to TiDB with minimal downtime
MySQL or Aurora → TiDB. We evaluate schema compatibility, configure full-load snapshot migration plus live incremental binlog sync using TiDB DM, validate data consistency, and cut over in a short, rehearsed window.
Technologies We Work With
Complete TiDB ecosystem and integration tools
TiDB HTAP & distributed SQL questions
Common questions about TiDB, MySQL compatibility, and horizontal scaling answered by senior DBREs.
Ready to Transform Your Data Infrastructure?
Contact us today to learn more about our TiDB services and how we can help you achieve your business goals with HTAP capabilities.
Compare with Other Databases
JusDB operates production fleets across most major engines. If you're weighing alternatives, here are the most common ones our customers compare against.
MySQL
TiDB is MySQL-wire-compatible. Most evaluations start here for migration scope and what query patterns will need refactoring.
PostgreSQL
Comparable distributed-SQL evaluation if you can absorb a wire-protocol switch — Postgres has stronger JSON / window function support.
MongoDB
Sharded NoSQL is the historical alternative to distributed SQL — useful comparison when document model fits better than relational.
ScyllaDB
When the workload is write-heavy and CQL-shaped, ScyllaDB's shard-per-core architecture outperforms distributed SQL on the same hardware.
Explore Our TiDB Services
Explore more ways our TiDB experts can help with your database infrastructure.