Splunk to Kusto cheat sheet

Applies to: ✅ Azure Data Explorer ✅ Azure Monitor ✅ Microsoft Sentinel

This article is intended to assist users who are familiar with Splunk learn the Kusto Query Language to write log queries with Kusto. Direct comparisons are made between the two to highlight key differences and similarities, so you can build on your existing knowledge.

Structure and concepts

The following table compares concepts and data structures between Splunk and Kusto logs:

Concept	Splunk	Kusto	Comment
deployment unit	cluster	cluster	Kusto allows arbitrary cross-cluster queries. Splunk doesn't.
data caches	buckets	caching and retention policies	Controls the period and caching level for the data. This setting directly affects the performance of queries and the cost of the deployment.
logical partition of data	index	database	Allows logical separation of the data. Both implementations allow unions and joining across these partitions.
structured event metadata	N/A	table	Splunk doesn't expose the concept of event metadata to the search language. Kusto logs have the concept of a table, which has columns. Each event instance is mapped to a row.
record	event	row	Terminology change only.
record attribute	field	column	In Kusto, this setting is predefined as part of the table structure. In Splunk, each event has its own set of fields.
types	datatype	datatype	Kusto data types are more explicit because they're set on the columns. Both have the ability to work dynamically with data types and roughly equivalent set of datatypes, including JSON support.
query and search	search	query	Concepts essentially are the same between Kusto and Splunk.
event ingestion time	system time	ingestion_time()	In Splunk, each event gets a system timestamp of the time the event was indexed. In Kusto, you can define a policy called ingestion_time that exposes a system column that can be referenced through the ingestion_time() function.

Functions

The following table specifies functions in Kusto that are equivalent to Splunk functions.

Splunk	Kusto	Comment
strcat	strcat()	(1)
split	split()	(1)
if	iff()	(1)
tonumber	todouble() tolong() toint()	(1)
upper lower	toupper() tolower()	(1)
replace	replace_string(), replace_strings() or replace_regex()	(1) Although replace functions take three parameters in both products, the parameters are different.
substr	substring()	(1) Also note that Splunk uses one-based indices. Kusto notes zero-based indices.
tolower	tolower()	(1)
toupper	toupper()	(1)
match	matches regex	(2)
regex	matches regex	In Splunk, regex is an operator. In Kusto, it's a relational operator.
searchmatch	==	In Splunk, searchmatch allows searching for the exact string.
random	rand() rand(n)	Splunk's function returns a number between zero to 231-1. Kusto's returns a number between 0.0 and 1.0, or if a parameter is provided, between 0 and n-1.
now	now()	(1)
relative_time	totimespan()	(1) In Kusto, Splunk's equivalent of relative_time(datetimeVal, offsetVal) is datetimeVal + totimespan(offsetVal). For example, search | eval n=relative_time(now(), "-1d@d") becomes ... | extend myTime = now() - totimespan("1d").

(1) In Splunk, the function is invoked by using the eval operator. In Kusto, it's used as part of extend or project.
(2) In Splunk, the function is invoked by using the eval operator. In Kusto, it can be used with the where operator.

Operators

The following sections give examples of how to use different operators in Splunk and Kusto.

Search

In Splunk, you can omit the search keyword and specify an unquoted string. In Kusto, you must start each query with find, an unquoted string is a column name, and the lookup value must be a quoted string.

Product	Operator	Example
Splunk	search	search Session.Id="c8894ffd-e684-43c9-9125-42adc25cd3fc" earliest=-24h
Kusto	find	find Session.Id=="c8894ffd-e684-43c9-9125-42adc25cd3fc" and ingestion_time()> ago(24h)

Filter

Kusto log queries start from a tabular result set in which filter is applied. In Splunk, filtering is the default operation on the current index. You also can use the where operator in Splunk, but we don't recommend it.

Product	Operator	Example
Splunk	search	Event.Rule="330009.2" Session.Id="c8894ffd-e684-43c9-9125-42adc25cd3fc" _indextime>-24h
Kusto	where	Office_Hub_OHubBGTaskError | where Session_Id == "c8894ffd-e684-43c9-9125-42adc25cd3fc" and ingestion_time() > ago(24h)

Get n events or rows for inspection

Kusto log queries also support take as an alias to limit. In Splunk, if the results are ordered, head returns the first n results. In Kusto, limit isn't ordered, but it returns the first n rows that are found.

Product	Operator	Example
Splunk	head	Event.Rule=330009.2 | head 100
Kusto	limit	Office_Hub_OHubBGTaskError | limit 100

Get the first n events or rows ordered by a field or column

For the bottom results, in Splunk, you use tail. In Kusto, you can specify ordering direction by using asc.

Product	Operator	Example
Splunk	head	Event.Rule="330009.2" | sort Event.Sequence | head 20
Kusto	top	Office_Hub_OHubBGTaskError | top 20 by Event_Sequence

Extend the result set with new fields or columns

Splunk has an eval function, but it's not comparable to the eval operator in Kusto. Both the eval operator in Splunk and the extend operator in Kusto support only scalar functions and arithmetic operators.

Product	Operator	Example
Splunk	eval	Event.Rule=330009.2 | eval state= if(Data.Exception = "0", "success", "error")
Kusto	extend	Office_Hub_OHubBGTaskError | extend state = iff(Data_Exception == 0,"success" ,"error")

Rename

Kusto uses the project-rename operator to rename a field. In the project-rename operator, a query can take advantage of any indexes that are prebuilt for a field. Splunk has a rename operator that does the same.

Product	Operator	Example
Splunk	rename	Event.Rule=330009.2 | rename Date.Exception as execption
Kusto	project-rename	Office_Hub_OHubBGTaskError | project-rename exception = Date_Exception

Format results and projection

Splunk uses the table command to select which columns to include in the results. Kusto has a project operator that does the same and more.

Product	Operator	Example
Splunk	table	Event.Rule=330009.2 | table rule, state
Kusto	project	Office_Hub_OHubBGTaskError | project exception, state

Splunk uses the fields - command to select which columns to exclude from the results. Kusto has a project-away operator that does the same.

Product	Operator	Example
Splunk	fields -	Event.Rule=330009.2 | fields - quota, hightest_seller
Kusto	project-away	Office_Hub_OHubBGTaskError | project-away exception, state

Aggregation

See the list of summarize aggregations functions that are available.

Splunk operator	Splunk example	Kusto operator	Kusto example
stats	search (Rule=120502.*) | stats count by OSEnv, Audience	summarize	Office_Hub_OHubBGTaskError | summarize count() by App_Platform, Release_Audience
evenstats	... | stats count_i by time, category | eventstats sum(count_i) AS count_total by _time_	join	T2 | join kind=inner (T1) on _time | project _time, category, count_i, count_total

Join

join in Splunk has substantial limitations. The subquery has a limit of 10,000 results (set in the deployment configuration file), and a limited number of join flavors are available.

Product	Operator	Example
Splunk	join	Event.Rule=120103* | stats by Client.Id, Data.Alias | join Client.Id max=0 [search earliest=-24h Event.Rule="150310.0" Data.Hresult=-2147221040]
Kusto	join	cluster("OAriaPPT").database("Office PowerPoint").Office_PowerPoint_PPT_Exceptions | where Data_Hresult== -2147221040 | join kind = inner (Office_System_SystemHealthMetadata | summarize by Client_Id, Data_Alias)on Client_Id

Sort

The default sort order is ascending. To specify descending order, add a minus sign (-) before the field name. Kusto also supports defining where to put nulls, either at the beginning or at the end.

Product	Operator	Example
Splunk	sort	Event.Rule=120103 | sort -Data.Hresult
Kusto	order by	Office_Hub_OHubBGTaskError | order by Data_Hresult, desc

Multivalue expand

The multivalue expand operator is similar in both Splunk and Kusto.

Product	Operator	Example
Splunk	mvexpand	mvexpand solutions
Kusto	mv-expand	mv-expand solutions

Result facets, interesting fields

In Log Analytics in the Azure portal, only the first column is exposed. All columns are available through the API.

Product	Operator	Example
Splunk	fields	Event.Rule=330009.2 | fields App.Version, App.Platform
Kusto	facets	Office_Excel_BI_PivotTableCreate | facet by App_Branch, App_Version

Deduplicate

In Kusto, you can use summarize arg_min() to reverse the order of which record is chosen.

Product	Operator	Example
Splunk	dedup	Event.Rule=330009.2 | dedup device_id sortby -batterylife
Kusto	summarize arg_max()	Office_Excel_BI_PivotTableCreate | summarize arg_max(batterylife, *) by device_id

Related content

• Walk through a tutorial on the Kusto Query Language.