Splunk to Kusto cheat sheet

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.


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()
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()
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.


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


In the following examples, the Splunk field rule maps to a table in Kusto, and Splunk's default timestamp maps to the Logs Analytics ingestion_time() column.

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)


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")


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 field - 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


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 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


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


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