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Data processing and pipelines
ingestion
ETL / data ingestion pipeline
Airbyte, Fivetran
System
Techniques · 12
Primitives · 52
ingestion
Deterministic simulation testing
distributed · medium: Run the whole system in one thread under a seeded scheduler with simulated network, disk and clock, so every failure replays from its seed.
›
Primary-backup replication
distributed · medium: One node orders all writes and ships them to standbys; the acknowledgement rule (none, one, all) sets what a crash loses, and an external arbiter decides who takes over.
›
Coverage-guided fuzzing
security · medium: Mutate inputs, run an instrumented target, and keep any input that reaches a new code edge; feedback turns blind guessing into incremental search.
›
Change data capture
storage · medium: Decode the database's own commit log into row-change events in commit order, with a resume position, so any consumer can mirror the data exactly.
›
Point-in-time recovery
storage · medium: Periodic base backups plus a continuously archived change log let you rebuild the state as of any instant, then branch from there.
›
Schema evolution
storage · medium: Compatibility rules (backward/forward/full) for adding, removing and renaming fields
Delta debugging
compilers · medium: Ddmin minimization of failing inputs or change sets
Consumer offsets
distributed · low: Each consumer group stores one integer per partition, the next position to read, so a restarted consumer resumes where it left off with at-least-once delivery.
›
Cursor pagination
networking · low: Keyset/opaque-cursor pagination for stable incremental reads from APIs and tables
Hdr histogram
data-structures · low: Log-linear bucketed histograms with bounded relative error for latency percentiles
Dead-letter queue
distributed · low: A side queue for messages that keep failing: after N delivery attempts or a permanent error, park them with the reason so the main queue keeps moving.
›
Idempotency keys
finance · low: Client-chosen unique key per logical operation, stored with a request fingerprint and the final response, so retries replay the first result instead of acting twice.
›
Process supervision
hardware-os · low: A parent process starts services, reaps their exits and restarts them under a delay and burst-limit policy, then stops them with SIGTERM before SIGKILL.
›
Mutual TLS
security · low: TLS where the client also proves a certificate key, so every connection carries a verified, rotatable machine identity.
›
OAuth 2 and OpenID Connect
security · low: Delegated authorization (OAuth 2) and login on top of it (OIDC); use authorization code + PKCE for every user-facing client.
›
Secrets management
security · low: Keep keys and passwords out of code and logs, give workloads short-lived identity instead of static keys, and make rotation routine.
›
Chunked backfill
storage · low: Process old data in bounded key ranges, one short transaction per chunk, with a saved checkpoint and idempotent writes, so a crash resumes and live traffic never waits.
›
Columnar file format
storage · low: Row groups, column chunks, pages, encodings and footer stats (Parquet/ORC style) (listed in Moved to the wiki)
Upsert merge
storage · low: MERGE/upsert by key with deduplication and late-arriving data rules
Exponential backoff with jitter
systems · low: Retry after delays that grow geometrically and are randomized, so failed clients spread out instead of hammering a recovering service in synchronized waves.
›
Graceful draining
systems · low: On a termination signal, stop taking new work, finish in-flight work until a deadline, tell clients to reconnect elsewhere, then exit; clients resume from a token.
›
Token bucket
systems · low: A bucket of up to b tokens refilled at rate r; requests spend tokens, enforcing an average rate while allowing bursts of b.
›
Cooperative scheduling
concurrency · low: Green threads/coroutines yielding at await points on a user-space scheduler
+ 5 more techniques
+ 36 more primitives
System
Techniques · 12
Primitives · 52
ingestion
Deterministic simulation testing
distributed · medium: Run the whole system in one thread under a seeded scheduler with simulated network, disk and clock, so every failure replays from its seed.
›
Primary-backup replication
distributed · medium: One node orders all writes and ships them to standbys; the acknowledgement rule (none, one, all) sets what a crash loses, and an external arbiter decides who takes over.
›
Coverage-guided fuzzing
security · medium: Mutate inputs, run an instrumented target, and keep any input that reaches a new code edge; feedback turns blind guessing into incremental search.
›
Change data capture
storage · medium: Decode the database's own commit log into row-change events in commit order, with a resume position, so any consumer can mirror the data exactly.
›
Point-in-time recovery
storage · medium: Periodic base backups plus a continuously archived change log let you rebuild the state as of any instant, then branch from there.
›
Schema evolution
storage · medium: Compatibility rules (backward/forward/full) for adding, removing and renaming fields
Delta debugging
compilers · medium: Ddmin minimization of failing inputs or change sets
Fault injection
distributed · medium: Inject latency, errors, kills and partitions via proxies, netem or hooks
Incremental sync cursors
distributed · medium: The client keeps one opaque token; each pull returns only the changes after it plus the next token, so sync cost scales with what changed, not with the dataset.
›
ARIES recovery
storage · medium: Three-pass crash recovery (analysis, redo, undo) for steal/no-force buffer pools; repeats history, then rolls back losers with compensation log records.
›
Syscall interception
security · medium: Intercept syscalls via ptrace, seccomp user notify or a user-space kernel
Buffer pool
storage · medium: The database's own page cache (frames, page table, pin counts, dirty bits, replacement) so it, not the OS, controls eviction, write order and I/O.
›
Consumer offsets
distributed · low: Each consumer group stores one integer per partition, the next position to read, so a restarted consumer resumes where it left off with at-least-once delivery.
›
Cursor pagination
networking · low: Keyset/opaque-cursor pagination for stable incremental reads from APIs and tables
Hdr histogram
data-structures · low: Log-linear bucketed histograms with bounded relative error for latency percentiles
Dead-letter queue
distributed · low: A side queue for messages that keep failing: after N delivery attempts or a permanent error, park them with the reason so the main queue keeps moving.
›
Idempotency keys
finance · low: Client-chosen unique key per logical operation, stored with a request fingerprint and the final response, so retries replay the first result instead of acting twice.
›
Process supervision
hardware-os · low: A parent process starts services, reaps their exits and restarts them under a delay and burst-limit policy, then stops them with SIGTERM before SIGKILL.
›
Mutual TLS
security · low: TLS where the client also proves a certificate key, so every connection carries a verified, rotatable machine identity.
›
OAuth 2 and OpenID Connect
security · low: Delegated authorization (OAuth 2) and login on top of it (OIDC); use authorization code + PKCE for every user-facing client.
›
Secrets management
security · low: Keep keys and passwords out of code and logs, give workloads short-lived identity instead of static keys, and make rotation routine.
›
Chunked backfill
storage · low: Process old data in bounded key ranges, one short transaction per chunk, with a saved checkpoint and idempotent writes, so a crash resumes and live traffic never waits.
›
Columnar file format
storage · low: Row groups, column chunks, pages, encodings and footer stats (Parquet/ORC style) (listed in Moved to the wiki)
Upsert merge
storage · low: MERGE/upsert by key with deduplication and late-arriving data rules
Exponential backoff with jitter
systems · low: Retry after delays that grow geometrically and are randomized, so failed clients spread out instead of hammering a recovering service in synchronized waves.
›
Graceful draining
systems · low: On a termination signal, stop taking new work, finish in-flight work until a deadline, tell clients to reconnect elsewhere, then exit; clients resume from a token.
›
Token bucket
systems · low: A bucket of up to b tokens refilled at rate r; requests spend tokens, enforcing an average rate while allowing bursts of b.
›
Cooperative scheduling
concurrency · low: Green threads/coroutines yielding at await points on a user-space scheduler
Record replay
distributed · low: Record every nondeterministic input (time, randomness, I/O, model and tool outputs, per-tick player input) and re-execute deterministically for debugging, replays and state rebuild
PRNGs (PCG, xoshiro)
numerics · low: Small, fast, statistically strong non-cryptographic generators: PCG32 and xoshiro256**, with seeding, parallel streams and unbiased ranges.
›
Leases
distributed · low: A lock that expires on its own: bounded-time ownership that survives crashes and partitions, given bounded clock drift and fencing tokens on writes.
›
Write-ahead log
storage · low: Append each change to a checksummed sequential log and fsync it before touching data pages; the basis of crash durability in nearly every database.
›
Health checking
systems · low: Decide per backend whether to route to it using probes and real-traffic errors, with consecutive-count hysteresis, capped ejection and a panic fallback.
›
Code coverage instrumentation
compilers · low: Insert counters into compiled code to record which blocks, edges or lines ran; a spanning tree of the control-flow graph cuts the counters needed.
›
Fast hash functions
data-structures · low: Non-cryptographic hashes built from 64×64→128-bit multiplies and xor-shifts; pick by key size, trust level and whether the hash is persisted.
›
Sanitizers
security · low: ASan/UBSan/TSan shadow memory and instrumentation to catch memory bugs
Message sequence numbers
distributed · low: A per-stream counter on every message lets the receiver detect loss, duplicates and reordering, ack cheaply and resume after reconnect with "send from N".
›
Object storage
cloud · low: S3-compatible blob storage at cents per GB-month with 11 nines durability; pick by egress price, request price and latency, not by storage price alone.
›
Copy on write snapshots
storage · low: Point-in-time snapshots by sharing pages/extents and copying only on write
Protobuf wire format
networking · low: Protocol Buffers wire format: tags, varints, length-delimited fields and schema evolution
JSON Schema validation
security · low: Compile a JSON Schema once, then check every untrusted document against it, within hard size and depth limits, and report failures as JSON Pointers.
›
Failure bisection
search-sort · low: Binary search over commits, batches or inputs to isolate a failure
Transparent interception
networking · low: Redirect traffic to a local proxy (iptables TPROXY/REDIRECT, eBPF) without app changes
Ebpf
hardware-os · low: Verified in-kernel programs on hooks (kprobes, XDP, tc) with maps
Ptrace process control
hardware-os · low: Ptrace: attach, read and write registers and memory, single-step, intercept signals
Seccomp bpf
security · low: Syscall filtering with seccomp BPF programs
fsync, O_DSYNC and O_DIRECT
hardware-os · low: What fsync, fdatasync, O_DSYNC, O_DIRECT and F_FULLFSYNC really guarantee on Linux and macOS, and the exact call sequences for crash-safe files.
›
LRU and CLOCK
systems · low: LRU evicts the least recently used entry via hash map plus linked list; CLOCK approximates it with a reference bit, so hits take no lock.
›
S3-FIFO
systems · low: Three FIFO queues (small, main, ghost) that evict one-hit wonders quickly and keep reused objects; low miss ratios with no list moves on hits.
›
Control-flow graph
compilers · low: Split a linear instruction list into basic blocks and connect them by jumps; the graph every optimizer, SSA builder and dataflow pass walks.
›
d-ary heap
data-structures · low: Array heap with d children per node (d = 4 typical): half the binary heap's depth, siblings in one cache line, faster priority queues.
›
Fencing tokens
distributed · low: A number that grows with every lock grant and is checked by the protected resource, so a paused ex-holder's late write is rejected.
›
Segmented log
distributed · low: Split an append-only log into files named by their first offset, write only the newest, and find any record by binary search plus a sparse index.
›
BFS and DFS
graphs · low: The two basic graph traversals; BFS gives hop distances and levels, DFS gives discovery/finish order for cycles, components and topological order.
›
Minimum spanning tree
graphs · low: Cheapest set of edges connecting all vertices; Kruskal sorts edges and joins components with union-find, Prim grows one tree, Boruvka merges in parallel rounds.
›
Union-find
graphs · low: Disjoint-set forest with union by size and path compression; merges sets and answers same-set queries in effectively constant time.
›
CRC32C checksums
hardware-os · low: The Castagnoli CRC-32 with dedicated instructions on x86 (SSE4.2) and ARMv8. It is the standard fast integrity check for storage blocks, logs and network frames.
›
SIMD programming
hardware-os · low: Process 4-16 lanes per instruction with AVX2, AVX-512 or NEON via Rust std::arch, with runtime dispatch and a portable fallback.
›
Sparse matrices (CSR)
numerics · low: Compressed sparse row stores only nonzeros as row pointers, column indices and values; SpMV streams them once, so it is memory-bandwidth bound.
›
AEAD (AES-GCM, ChaCha20-Poly1305)
security · low: Authenticated encryption that encrypts and detects tampering in one call; the only kind of symmetric encryption you should use.
›
Constant time code
security · low: Writing secret-dependent code without branches or memory lookups on secrets; constant-time compare and select
Cryptographic hashes (SHA-2, BLAKE3)
security · low: Collision-resistant fingerprints of data; SHA-256 for interoperability, BLAKE3 for speed, HMAC/HKDF for keyed uses.
›
Csprng
security · low: OS-backed cryptographically secure random numbers (getrandom), and when a fast PRNG is not enough
JSON Web Token (JWT)
security · low: A signed, URL-safe token carrying claims; the verifier's job is the checklist (pinned algorithm, key by kid, exp, aud, iss), not the format.
›
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