Load Testing Tools

Grinder

TCP proxy - records network activity into the Grinder test script
Distributed testing - can scale with the increasing number of agent instances
Power of Python or Closure combined with any Java API for test script creation or modification
Flexible parameterization which includes creating test data on-the-fly and the capability to use external data sources like files, databases, etc.
Post processing and assertion - full access to test results for correlation and content verification
Support of multiple protocols

HTTP Recorder
An expressive self-explanatory DSL for test development
Scala-based
Produces higher load by using an asynchronous non-blocking approach
Full support of HTTP(S) protocols & can also be used for JDBC and JMS load testing
Multiple input sources for data-driven tests
Powerful and flexible validation and assertions system
Comprehensive informative load reports

Distributed by design
High performance. Underlying multithreaded-oriented Erlang architecture enables the simulation of thousands of virtual users on mid-end developer machines
Support of multiple protocols
A test recorder which supports HTTP and Postgres
OS monitoring. Both the load generator and application under the test operating system metrics can be collected via several protocols
Dynamic scenarios and mixed behaviours. The flexible load scenarios definition mechanism allows for any number of load patterns to be combined in a single test
Post processing and correlation
External data sources for data driven testing
Embedded easy-readable load reports which can be collected and visualized during load

Cross-platform. JMeter can be run on any operating system with Java
Scalable. When you need to create a higher load than a single machine can create, JMeter can be executed in a distributed mode - meaning one master JMeter machine will control a number of remote hosts.
Multi-protocol support. The following protocols are all supported ‘out-of-the-box’: HTTP, SMTP, POP3, LDAP, JDBC, FTP, JMS, SOAP, TCP
Multiple implementations of pre and post processors around sampler. This provides advanced setup, teardown parametrization and correlation capabilities
Various assertions to define criteria
Multiple built-in and external listeners to visualize and analyze performance test results
Integration with major build and continuous integration systems - making JMeter performance tests part of the full software development life cycle