Above 10 TB, storage becomes an engineering problem of its own. Transfer windows are measured in days, cost grows with access frequency, and deletion is usually not an option. Secure storage and big-data management at enterprise scale.
Capacity alone is not the answer. Tiering, transfer, access control and recovery are part of the same design.
The service is designed from ten terabytes up to petabyte scale. Growing capacity is an expansion of the existing setup, not a new deployment.
The same data set lives across three tiers by access frequency rather than in a single store. Moving between tiers does not change the address your application uses.
Objects drop to a lower tier automatically based on age and access frequency. The rule is written once; after that nobody has to move files by hand.
Large objects are split into parts and uploaded in parallel. A failed part resumes where it stopped instead of restarting, which shortens the transfer window considerably.
Both single terabyte-sized files and bulk moves of millions of small objects are supported, each with its own transfer strategy.
What sits where is tracked in a catalogue: object metadata, tags and a search index. The archive stops being a pile nobody can describe.
Permissions are defined per folder and per object, not just per bucket. Teams, applications and external auditors each get their own key and their own scope.
For a defined period an object cannot be deleted or overwritten. Which key touched which object, when and how, is recorded in a form that cannot be altered.
The acceptable data-loss window and return-to-service time are set as targets, the recovery architecture is built around those two numbers, and a drill proves them.
Retention periods your industry mandates are expressed as policy. Deletion before the period ends is blocked; once it ends, cleanup runs automatically.
You decide where the data physically sits. KVKK and GDPR obligations are part of that decision and the choice is written into the contract.
Four questions about your data volume and how fast it grows. If the scale does not match, we will point you at something smaller.
Adding capacity does not stop the archive from growing; it only postpones the same problem. At this scale cost scales with access frequency, not with volume. Most of an archive is read a few times a year, and keeping that data on the fastest, most expensive tier buys you nothing.
Moving between tiers is not a manual job. Lifecycle policies push objects down by age and access frequency: same data, same address, same availability — with a materially lower retention cost.
Different industries, the same problem: the data keeps growing, most of it is rarely read, and none of it can be deleted.
Recordings written continuously, watched rarely, and searched backwards when an incident comes up. Legal retention usually blocks deletion as well.
Study files are part of the patient record: retained for many years, expected to be unalterable, and required to be findable quickly when needed.
High-frequency data streaming from line and machine sensors. Day-to-day use needs a few days; root-cause analysis needs years of history.
Application, security and access logs. Daily operations read the last few days; audits and incident reviews ask for much older material.
Backups pile up version by version and are the fastest-growing part of the archive. Without tiering they keep sitting on the most expensive storage.
Each step has a defined output. You never have to ask where the project stands.
How much data exists, how it grows, which portion is read how often — the archive's real access pattern is measured. Tier decisions rest on that data.
Which data sits in which tier, and under what condition it drops down, is written as a rule; legal retention periods are encoded into those rules.
Whether the first move runs over the wire or by physical disk is decided from volume and link capacity; either way you get the schedule up front.
Per-team and per-application keys, object-level permissions, immutable retention rules and audit trail logging all go live.
The agreed RPO and RTO targets are tested with a real recovery scenario. The result is reported; if the targets are missed, the architecture is revised.
Tier based
Billing is calculated from how much data sits in which tier, not from raw total volume. As lifecycle rules run, the distribution shifts in your favour on its own.
Transfer is its own line
The method and duration of the initial move are set after measurement and appear as a separate line in the quote. There is no setup cost hidden inside the monthly fee.
Commitments in a 12-month contract
RPO, RTO, retention period and data location are written into the contract as numbers and place names. "We have backups" is not a commitment. The contract runs 12 months: unit pricing holds steady through the year, and at the end of it scope and price are reviewed together against the grown archive and signed again.
It is built for archives above 10 TB. Below that, the S3 storage and backup package is both faster to set up and more economical; when the scale grows, you move onto this structure.
Adding disk only buys capacity — it does not change the access pattern. Most of an archive is read a few times a year, and keeping that data on the most expensive tier buys you nothing. At this scale cost scales with access frequency rather than volume, and that is exactly what tiering targets.
The archive tier has retrieval latency — the file becomes available after a scheduled retrieval, not instantly. That is why which data sits in which tier is decided together, after measuring your real access pattern.
It depends on volume and link capacity. If transferring over the wire will not finish in a reasonable window, physical disk shipping is planned. Either way, the schedule comes with the quote, after measurement.
For a defined period an object cannot be deleted or overwritten — not even with administrator rights. It is used for records under a legal retention obligation and as a defence against ransomware.
Which key touched which object, when, and what operation was performed. The records are held in a form that cannot be altered and can be exported for audit requests.
Yes. You choose between a Türkiye and a European Union location. Your KVKK and GDPR obligations are part of that decision and the choice is written into the contract.
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Moving a few hundred gigabytes is file copying. Data above 10 TB is an engineering problem: transfer windows are measured in days, single-part uploads fail, and cost scales with access frequency rather than raw size.
Camera footage, medical imaging archives, production telemetry, log accumulation and backup history all follow the same pattern — the data keeps growing, most of it is rarely read, and none of it can be deleted.
A hot tier holds daily-access data, a cold tier monthly, an archive tier yearly. Lifecycle policies move objects down automatically by age and access frequency — same data, same availability, materially lower cost.
Multipart parallel transfer, data cataloguing, object-level access control and an immutable audit trail are standard. On the recovery side, RPO and RTO targets are written into the contract as numbers.