jm + riak   24

Will the last person at Basho please turn out the lights? • The Register
Basho, once a rising star of the NoSQL database world, has faded away to almost nothing [...] According to sources, the company, which developed the Riak distributed database, has been shedding engineers for months, and is now operating as a shadow of its former self, as at least one buy-out has fallen through.
basho  riak  nosql  databases  storage  startups  funding 
4 weeks ago by jm
If Eventual Consistency Seems Hard, Wait Till You Try MVCC
ex-Percona MySQL wizard Baron Schwartz, noting that MVCC as implemented in common SQL databases is not all that simple or reliable compared to big bad NoSQL Eventual Consistency:
Since I am not ready to assert that there’s a distributed system I know to be better and simpler than eventually consistent datastores, and since I certainly know that InnoDB’s MVCC implementation is full of complexities, for right now I am probably in the same position most of my readers are: the two viable choices seem to be single-node MVCC and multi-node eventual consistency. And I don’t think MVCC is the simpler paradigm of the two.
nosql  concurrency  databases  mysql  riak  voldemort  eventual-consistency  reliability  storage  baron-schwartz  mvcc  innodb  postgresql 
december 2014 by jm
Great quote from Voldemort author Jay Kreps
"Reading papers: essential. Slavishly implementing ideas you read: not necessarily a good idea. Trust me, I wrote an Amazon Dynamo clone."

Later in the discussion, on complex conflict resolution logic (as used in Dynamo, Voldemort, and Riak):

"I reviewed 200 Voldemort stores, 190 used default lww conflict resolution. 10 had custom logic, all 10 of which had bugs." -- https://twitter.com/jaykreps/statuses/528292617784537088

(although IMO I'd prefer complex resolution to non-availability, when AP is required)
voldemort  jay-kreps  dynamo  cap-theorem  ap  riak  papers  lww  conflict-resolution  distcomp 
november 2014 by jm
Smart Clients, haproxy, and Riak
Good, thought-provoking post on good client library approaches for complex client-server systems, particularly distributed stores like Voldemort or Riak. I'm of the opinion that a smart client lib is unavoidable, and in fact essential, since the clients are part of the distributed system, personally.
clients  libraries  riak  voldemort  distsys  haproxy  client-server  storage 
october 2014 by jm
Roshiak
a Riak-based clone of Roshi, the CRDT server built on top of Redis. some day I'll write up the CRDT we use on top of Voldemort in $work.

Comments: https://lobste.rs/s/tim5xc
riak  roshi  crdt  redis  storage  time-series-data 
october 2014 by jm
Basho LevelDB supports tiered storage
Tiered storage is turning out to be a pretty practical trick to take advantage of SSDs:
The justification for two types/speeds of storage arrays is simple. leveldb is extremely write intensive in its lower levels. The write intensity drops off as the level number increases. Similarly, current and frequently updated data tends to be in lower levels while archival data tends to be in higher levels. These leveldb characteristics create a desire to have faster, more expensive storage arrays for the high intensity lower levels. This branch allows the high intensity lower levels to be on expensive storage arrays while slower, less expensive storage arrays to hold the higher level data to reduce costs.
caching  tiered-storage  storage  ssds  ebs  leveldb  basho  patches  riak  iops 
april 2014 by jm
TCP incast vs Riak
An extremely congested local network segment causes the "TCP incast" throughput collapse problem -- packet loss occurs, and TCP throughput collapses as a side effect. So far, this is pretty unsurprising, and anyone designing a service needs to keep bandwidth requirements in mind.

However it gets worse with Riak. Due to a bug, this becomes a serious issue for all clients: the Erlang network distribution port buffers fill up in turn, and the Riak KV vnode process (in its entirety) will be descheduled and 'cannot answer any more queries until the A-to-B network link becomes uncongested.'

This is where EC2's fully-uncontended-1:1-network compute cluster instances come in handy, btw. ;)
incast  tcp  networking  bandwidth  riak  architecture  erlang  buffering  queueing 
february 2014 by jm
Basho and Seagate partner to deliver scale-out cloud storage breakthrough
Ha, cool. Skip the OS, write the Riak store natively to the drive. This sounds frankly terrifying ;)
The Seagate Kinetic Open Storage platform eliminates the storage server tier of traditional data center architectures by enabling applications to speak directly to the storage system, thereby reducing expenses associated with the acquisition, deployment, and support of hyperscale storage infrastructures. The platform leverages Seagate’s expertise in hardware and software storage systems integrating an open source API and Ethernet connectivity with Seagate hard drive technology.
seagate  basho  riak  storage  hardware  drivers  os  ops 
october 2013 by jm
The trouble with timestamps
Timestamps, as implemented in Riak, Cassandra, et al, are fundamentally unsafe ordering constructs. In order to guarantee consistency you, the user, must ensure locally monotonic and, to some extent, globally monotonic clocks. This is a hard problem, and NTP does not solve it for you. When wall clocks are not properly coupled to the operations in the system, causal constraints can be violated. To ensure safety properties hold all the time, rather than probabilistically, you need logical clocks.
clocks  time  distributed  databases  distcomp  ntp  via:fanf  aphyr  vector-clocks  last-write-wins  lww  cassandra  riak 
october 2013 by jm
Gilt Tech
Gilt ran a stress-test of Riak to replace Voldemort (I think) in a shadow stack, with good results:
Riak’s strong performance suggests that, should we pursue implementation, it will withstand our unique traffic needs and prove reliable. As for the Gilt-Basho team’s strong performance: It was amazing that we were able to accomplish so much in just a week’s time! Thanks again to Seth and Steve for making this possible.
riak  testing  shadow-stack  voldemort  storage  gilt 
september 2013 by jm
how RAID fits in with Riak
Write heavy, high performance applications should probably use RAID 0 or avoid RAID altogether and consider using a larger n_val and cluster size. Read heavy applications have more options, and generally demand more fault tolerance with the added benefit of easier hardware replacement procedures.


Good to see official guidance on this (via Bill de hOra)
via:dehora  riak  cluster  fault-tolerance  raid  ops 
june 2013 by jm
Call me maybe: Carly Rae Jepsen and the perils of network partitions
Kyle "aphyr" Kingsbury expands on his slides demonstrating the real-world failure scenarios that arise during some kinds of partitions (specifically, the TCP-hang, no clear routing failure, network partition scenario). Great set of blog posts clarifying CAP
distributed  network  databases  cap  nosql  redis  mongodb  postgresql  riak  crdt  aphyr 
may 2013 by jm
Alex Feinberg's response to Damien Katz' anti-Dynamoish/pro-Couchbase blog post
Insightful response, worth bookmarking. (the original post is at http://damienkatz.net/2013/05/dynamo_sure_works_hard.html ).
while you are saving on read traffic (online reads only go to the master), you are now decreasing availability (contrary to your stated goal), and increasing system complexity.
You also do hurt performance by requiring all writes and reads to be serialized through a single node: unless you plan to have a leader election whenever the node fails to meet a read SLA (which is going to result a disaster -- I am speaking from personal experience), you will have to accept that you're bottlenecked by a single node. With a Dynamo-style quorum (for either reads or writes), a single straggler will not reduce whole-cluster latency.
The core point of Dynamo is low latency, availability and handling of all kinds of partitions: whether clean partitions (long term single node failures), transient failures (garbage collection pauses, slow disks, network blips, etc...), or even more complex dependent failures.
The reality, of course, is that availability is neither the sole, nor the principal concern of every system. It's perfect fine to trade off availability for other goals -- you just need to be aware of that trade off.
cap  distributed-databases  databases  quorum  availability  scalability  damien-katz  alex-feinberg  partitions  network  dynamo  riak  voldemort  couchbase 
may 2013 by jm
Riak, CAP, and eventual consistency
Good (albeit draft) write-up of the implications of CAP, allow_mult, and last_write_wins conflict-resolution policies in Riak:
As Brewer's CAP theorem established, distributed systems have to make hard choices. Network partition is inevitable. Hardware failure is inevitable. When a partition occurs, a well-behaved system must choose its behavior from a spectrum of options ranging from "stop accepting any writes until the outage is resolved" (thus maintaining absolute consistency) to "allow any writes and worry about consistency later" (to maximize availability). Riak leans toward the availability end of the spectrum, but allows the operator and even the developer to tune read and write requests to better meet the business needs for any given set of data.
riak  cap  eventual-consistency  distcomp  distributed-systems  partition  last-write-wins  voldemort  allow_mult 
april 2013 by jm
Boundary Techtalk - Large-scale OLAP with Kobayashi
Boundary on their TSD-on-Riak store.
Dietrich Featherston, Engineer at Boundary, walks through the process of designing Kobayashi, the time-series analytics database behind our network metrics. He goes through the false-starts and lessons learned in effectively using Riak as the storage layer for a large-scale OLAP database.  The system is ultimately capable of answering complex, ad-hoc queries at interactive latencies.
video  boundary  tsd  riak  eventual-consistency  storage  kobayashi  olap  time-series 
april 2013 by jm
Riak CS is now ASL2 open source
'Organizations and users can now access the source code on Github and download the latest packages from the downloads page. Also, today, we announced that Riak CS Enterprise is now available as commercial licensed software, featuring multi-datacenter replication technology and 24×7 Basho customer support.'
riak  riak-cs  nosql  storage  basho  open-source  github  apache  asl2 
march 2013 by jm
Riakking Complex Data Types
interesting details about Riak's support for secondary indexes. Not quite SQL, but still more powerful than plain old K/V storage (via dehora)
via:dehora  riak  indexes  storage  nosql  key-value-stores  2i  range-queries 
march 2013 by jm
Cassandra, Hive, and Hadoop: How We Picked Our Analytics Stack
reasonably good whole-stack performance testing and analysis; HBase, Riak, MongoDB, and Cassandra compared. Riak did pretty badly :(
riak  mongodb  cassandra  hbase  performance  analytics  hadoop  hive  big-data  storage  databases  nosql 
february 2013 by jm
Basho | Alert Logic Relies on Riak to Support Rapid Growth
'The new [Riak-based] analytics infrastructure performs statistical and correlation processing on all data [...] approximately 5 TB/day. All of this data is processed in real-time as it streams in. [...] Alert Logic’s analytics infrastructure, powered by Riak, achieves performance results of up to 35k operations/second across each node in the cluster – performance that eclipses the existing MySQL deployment by a large margin on single node performance. In real business terms, the initial deployment of the combination of Riak and the analytic infrastructure has allowed Alert Logic to process in real-time 7,500 reports, which previously took 12 hours of dedicated processing every night.'

Twitter discussion here: https://twitter.com/fisherpk/status/294984960849367040 , which notes 'heavily cached SAN storage, 12 core blades and 90% get to put ops', and '3 riak nodes, 12-cores, 30k get heavy riak ops/sec. 8 nodes driving ops to that cluster'. Apparently the use of SAN storage on all nodes is historic, but certainly seems to have produced good iops numbers as an (expensive) side-effect...
iops  riak  basho  ops  systems  alert-logic  storage  nosql  databases 
january 2013 by jm
LevelDB Benchmarks
nice results, particularly for sequential ops. will be a Riak backend vs InnoDB
leveldb  riak  databases  files  disk  google  storage  benchmarks 
july 2011 by jm

related tags

2i  alert-logic  alex-feinberg  algorithms  allow_mult  analytics  ap  apache  aphyr  architecture  asl2  availability  bandwidth  baron-schwartz  basho  benchmarks  big-data  boundary  buffering  caching  cap  cap-theorem  cassandra  cdt  client-server  clients  clocks  cluster  concurrency  conflict-resolution  consistency  couchbase  crdt  damien-katz  database  databases  disk  distcomp  distributed  distributed-databases  distributed-systems  distsys  drivers  dynamo  ebs  erlang  eventual-consistency  fault-tolerance  files  funding  gilt  github  google  hadoop  haproxy  hardware  hbase  hive  incast  indexes  innodb  iops  jay-kreps  key-value-stores  kobayashi  last-write-wins  leveldb  libraries  lww  manhattan  mongodb  mvcc  mysql  network  networking  nosql  ntp  olap  open-source  ops  os  papers  partition  partitions  patches  performance  postgresql  queueing  quorum  raid  range-queries  redis  reliability  replication  riak  riak-cs  roshi  scalability  seagate  shadow-stack  ssds  startups  storage  systems  tcp  testing  tiered-storage  time  time-series  time-series-data  tsd  tuning  twitter  vector-clocks  via:dehora  via:fanf  video  voldemort 

Copy this bookmark:



description:


tags: