We are excited to announce TokuDB® v6.5, the latest version of Tokutek’s flagship storage engine for MySQL and MariaDB.

This version offers optimization for Flash as well as more hot schema change operations for improved agility.

We’ll be posting more details about the new features and performance, so here’s an overview of what’s in store.

Flash

TokuDB v6.5 continues the great Toku-tradition of fast insertions. On flash drives, we show an order-of-magnitude (9x) faster insertion rate than InnoDB. TokuDB’s standard compression works just as well on flash and helps you get the most out of your storage system. And TokuDB reduces wear …

Businesses increasingly operate in a 24×7 environment, where complex analytics must be performed on live, continuously incoming “Big Data.” To address this, TokuDB has developed Fractal Tree®  technology, a revolutionary new indexing capability that enables SQL databases running advanced web applications to grow from gigabytes to terabytes while improving insert speed, query performance, compression, and enabling zero-downtime schema changes.

Date: September 5th
Time: 2 PM EST / 11 AM PST

REGISTER TODAY

TokuDB is used by MySQL and MariaDB customers worldwide to increase their database performance by 20x-80x on Big Data applications that conventional RDBMS’s cannot handle. Instead of waiting hours or even days to run queries …

I got a few questions like the ones below that I’d like to address to avoid further confusion.
How exactly secure is ClouSE for MySQL, the first secure database in the cloud? Am I protected against standard application level security attacks or even accidental admin mistakes?
With the help of ClouSE I get instantaneous backup for my database on the highly durable cloud storage. But how would I protect my data in case a malicious attack or an accident did occur?

Re: security

I’ve got a comment pointing out that data encryption on the storage level doesn’t protect from SQL injections.  Of course, data encryption does not protect from SQL injections (as long as there is SQL involved, there will be a risk of a SQL injection).  Neither does it protect from the infinite number …

A few weeks ago Bradley Kuszmaul and I attended the Dagstuhl Seminar on Database Workload Management.

The Dagstuhl computer science research center is (remotely) located in the countryside in Saarland, Germany. The actual building is an 18th Century Manor House, first retooled as an old-age home, and then a computer science research center. Workshop participants typically spend the whole week talking and working together.

Dagstuhl Computer Science Center

Shivnath Babu (Duke University), Goetz Graefe (Hewlett Packard), and Harumi Kuno (Hewlett Packard) did a great job organizing. …

Benchmarking is a tricky thing, especially when it comes to compression. Some data compresses quite well while other data does not compress at all. Storing jpeg images in a BLOB column produces 0% compression, but storing the string “AAAAAAAAAAAAAAAAAAAA” in a VARCHAR(20) column produces extremely high (and unrealistic) compression numbers.

This week I was assisting a TokuDB customer understand the insertion performance of TokuDB versus InnoDB and MyISAM for their actual data. The table contained a single VARCHAR(50), multiple INTEGER, one SET, one DECIMAL, and a surrogate primary key.  To support a varied query workload they needed 6 indexes.

Here is an obfuscated schema of the table:

col1 varchar(50) NOT NULL,
col2 int(40) NOT NULL DEFAULT '0',
col3 int(10) NOT NULL DEFAULT '0',
col4 int(10) NOT NULL DEFAULT '0',
col5 int(10) NOT NULL DEFAULT '0',
col6 set('val1', 'val2', ..., ‘val19’, 'val20',) NOT NULL DEFAULT …

Three rules on making indexes around queries to provide good performance

Application performance often depends on how fast a query can respond and query performance almost always depends on good indexing. So one of the quickest and least expensive ways to increase application performance is to optimize the indexes. This talk presents three simple and effective rules on how to construct indexes around queries that result in good performance.

Time: 2PM EDT / 11AM PDT

This webinar is a general discussion applicable to all databases using indexes and is not specific to any particular MySQL® storage engine (e.g., InnoDB, TokuDB®, etc.). The rules are explained using a simple model that does NOT rely on understanding B-trees, Fractal Tree® indexing, …

We found a simple XA transaction that crashes MySQL 5.5 replication. This simple transaction inserts a row into an InnoDB table and a TokuDB table. The bug was caused by a flaw in the logging code exposed by the transaction’s use of two XA storage engines (TokuDB and InnoDB). This bug was fixed in the TokuDB 6.0.1 release.

Here are some details.  Suppose that a database contains the following tables.

create table t1 (a int) engine=InnoDB
create table t2 (a int) engine=TokuDB

 The following transaction

begin
insert into t1 values (1)
insert into t2 values (2)
commit

causes the replication slave to crash.

The crash occurs when mysqld tries to dereference a NULL pointer.

#4  0x000000000088e203 in MYSQL_BIN_LOG::log_and_order (this=0x14b8640, thd=0x7f7758000af0, xid=161, all=true, need_prepare_ordered=false, need_commit_ordered=true) at …

Solving the Challenges of Big Databases with MySQL

When you’re using MySQL for big data (more than ten times as large as main memory), these challenges often arise: loading data fast; maintaining indexes under insertions deletions, and updates; adding and removing columns online; adding indexes online; preventing slave lag; and compressing data effectively.

This session shows why some of these challenges are difficult to solve with storage engines based on B-trees, how Fractal Tree® data structures work, and why they can help solve these problems. Tokutek sells a transaction-safe Fractal Tree storage engine for MySQL, but the presentation is primarily about the underlying technology. It includes a discussion of both the theoretical and practical aspects of Fractal Tree indexes.

I have the privilege of being able to give this talk at both conferences, so please stop by my presentation at …

In my last post, I wrote that I observed many similarities between TokuDB and MySQL Cluster. Many features that benefit TokuDB also benefit MySQL Cluster, and vice versa, with Hot Column Addition and Deletion (HCAD) being an example. Over my next few posts, I expand on some more of these possibly unexpected similarities.

Today I want to focus on optimizer support for clustering keys. Both MySQL Cluster and TokuDB can benefit from the MySQL optimizer supporting clustering keys. For TokuDB, the benefit is obvious, as TokuDB supports clustering keys. A non-negligible part of our effort is changing the …

Table optimization is a necessary evil; tables sometimes need to be optimized to reclaim space or to improve query performance.  Unfortunately, MySQL blocks writes to a table while it is being optimized.  Because optimization time is proportional to the table size, writes can be blocked for a long time.  Fractal Tree indexes support online optimization; however, the MySQL metadata lock gets in the way of writing while optimizing.  We will describe a simple patch to MySQL that enables online optimization of TokuDB tables.

Why do tables need to be optimized?  Here are some reasons.

• Insertions with random keys can result in a tree with underutilized leaf blocks.  Many tree algorithms split nodes in half when they become full.  If these nodes are stored in fixed sized blocks, like many B-trees do, then there can be a lot of wasted space.  Table optimization of B-trees write blocks with less …