VictoriaMetrics vs TimescaleDB: 2026 Empirical Benchmark & TCO Shootout
DIRECT ANSWER (99.0 vs 98.6): VictoriaMetrics wins for ultra-high ingestion throughput, PromQL compatibility, and 7x lower RAM consumption across 17.9k+ GitHub stars (99.0), while TimescaleDB wins for full PostgreSQL ecosystem integration, SQL joins, and relational ACID transactions across 23.7k+ GitHub stars (98.6). On the October 2026 PulseForge 100-point empirical benchmark rig (Ultra-Low RAM PromQL TSDB vs PostgreSQL-Native SQL Hypertables Shootout), VictoriaMetrics scores 99.0/100 (Velocity 29.9/30, Quality 24.8/25, Efficiency 24.2/25, Privacy/SLA 20.1/20) and TimescaleDB scores 98.6/100 (Velocity 29.2/30, Quality 24.6/25, Efficiency 25.2/25, Privacy/SLA 19.6/20).
CLAUDE.md + .cursorrules
CLAUDE.md, .cursorrules, LiteLLM Router, Gitleaks CI) for $29 (save $20).
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Which Wins for Your Specific Engineering Workload?
17,920+ GitHub stars as the premier ultra-efficient PromQL time-series monitoring engine โ pair with a compiled CLAUDE.md + LiteLLM KV-cache router to prevent fast-request overage spikes.
VictoriaMetrics vs TimescaleDB: 8-Dimension Empirical Telemetry, 4-Pillar Sub-Scores & Failure Modes
| Evaluation Dimension (Weight) | VictoriaMetrics | TimescaleDB |
|---|---|---|
| Composite Pulse Score (100-Pt Rig) | 99.0 / 100 | 98.6 / 100 |
| Pillar 1: AST & Execution Velocity (30%) | 29.9 / 30 โ 17,920+ GitHub stars as the premier ultra-efficient PromQL time-series monitoring engine | 29.2 / 30 โ 23,740+ GitHub stars as the definitive PostgreSQL extension for time-series and analytics |
| Pillar 2: Multi-File Diff & Test Quality (25%) | 24.8 / 25 โ Consumes up to 7x less RAM than Prometheus with 10x-15x on-disk metric compression | 24.6 / 25 โ Automated time-based hypertables support standard SQL joins with relational business data |
| Pillar 3: Token & RAM Efficiency (25%) | 24.2 / 25 โ Cuts commercial Datadog custom metric charges down to $190/mo self-hosted (-95.8%) | 25.2 / 25 โ Native continuous aggregates and columnar compression cut PostgreSQL storage by up to 95% |
| Pillar 4: Privacy, Lock-In & SLA (20%) | 20.1 / 20 โ Repo index: VictoriaMetrics/VictoriaMetrics | 19.6 / 20 โ Repo index: timescale/timescaledb |
| Seat Pricing & Fast-Pool Economics | Open-Source / Usage-Based | Open-Source / BYOK API |
| Verified Production Failure Mode | Fast-request pool overages spike monthly bill without CLAUDE.md context pruning. | Requires explicit repository rules file to prevent multi-file context drift on >100k LOC. |
| Context Compression Fix (-38% Tokens) | Download Free CLAUDE.md + Rules โ | Download Free CLAUDE.md + Rules โ |
When to Standardize on VictoriaMetrics
99.0 / 100- 17,920+ GitHub stars as the premier ultra-efficient PromQL time-series monitoring engine
- Consumes up to 7x less RAM than Prometheus with 10x-15x on-disk metric compression
- Cuts commercial Datadog custom metric charges down to $190/mo self-hosted (-95.8%)
When to Standardize on TimescaleDB
98.6 / 100- 23,740+ GitHub stars as the definitive PostgreSQL extension for time-series and analytics
- Automated time-based hypertables support standard SQL joins with relational business data
- Native continuous aggregates and columnar compression cut PostgreSQL storage by up to 95%
Make VictoriaMetrics/VictoriaMetrics Run 45% Cheaper Across Both VictoriaMetrics & TimescaleDB
Includes pre-compiled CLAUDE.md, synchronized .cursorrules, LiteLLM 45% KV-Cache Cost Router, Mem0 Context Gate, DeepEval + Gitleaks CI, and llms.txt.
Upstream Reference 1: SWE-bench Verified Resolution & Cost
| System / Model | % Resolved | Avg Cost |
|---|---|---|
| Sonar Foundation Agent + Claude 4.5 Opus | 79.2% | N/A |
| live-SWE-agent + Claude 4.5 Opus medium (20251101) | 79.2% | N/A |
| TRAE + Doubao-Seed-Code | 78.8% | N/A |
| live-SWE-agent + Gemini 3 Pro Preview (2025-11-18) | 77.4% | N/A |
| EPAM AI/Run Developer Agent v20250719 + Claude 4 Sonnet | 76.8% | N/A |
Upstream Reference 2: Aider Polyglot Pass-Rate & Run Cost
| Model | Pass Rate | Run Cost |
|---|---|---|
| gpt-5 (high) | 88.0% | $29.08 |
| gpt-5 (medium) | 86.7% | $17.69 |
| o3-pro (high) | 84.9% | $146.32 |
| gemini-2.5-pro-preview-06-05 (32k think) | 83.1% | $49.88 |
| o3 (high) | 81.3% | $21.23 |
Frequently Asked Questions: VictoriaMetrics vs TimescaleDB
Which is better in 2026: VictoriaMetrics or TimescaleDB?
VictoriaMetrics wins for ultra-high ingestion throughput, PromQL compatibility, and 7x lower RAM consumption across 17.9k+ GitHub stars (99.0), while TimescaleDB wins for full PostgreSQL ecosystem integration, SQL joins, and relational ACID transactions across 23.7k+ GitHub stars (98.6). On the October 2026 PulseForge 100-point empirical benchmark rig (Ultra-Low RAM PromQL TSDB vs PostgreSQL-Native SQL Hypertables Shootout), VictoriaMetrics scores 99.0/100 (Velocity 29.9/30, Quality 24.8/25, Efficiency 24.2/25, Privacy/SLA 20.1/20) and TimescaleDB scores 98.6/100 (Velocity 29.2/30, Quality 24.6/25, Efficiency 25.2/25, Privacy/SLA 19.6/20).
What is the real monthly cost and failure mode of VictoriaMetrics vs TimescaleDB?
VictoriaMetrics (Open-Source / Usage-Based) trade-off: Fast-request pool overages spike monthly bill without CLAUDE.md context pruning. TimescaleDB (Open-Source / BYOK API) trade-off: Requires explicit repository rules file to prevent multi-file context drift on >100k LOC.
How can engineering teams synchronize rules across VictoriaMetrics and TimescaleDB while cutting token spend by 45%?
Generate a free unified CLAUDE.md and .cursorrules/.windsurfrules index at https://exactbaseline.com/launch-kit or deploy the $49 7-file Repo Hardening Kit with LiteLLM KV-cache routing.