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DBMS > CrateDB vs. EXASOL vs. Manticore Search vs. Microsoft Azure Data Explorer vs. Splunk

System Properties Comparison CrateDB vs. EXASOL vs. Manticore Search vs. Microsoft Azure Data Explorer vs. Splunk

Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEXASOL  Xexclude from comparisonManticore Search  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSplunk  Xexclude from comparison
DescriptionDistributed Database based on LuceneHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Multi-storage database for search, including full-text search.Fully managed big data interactive analytics platformAnalytics Platform for Big Data
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSSearch engineRelational DBMS infocolumn orientedSearch engine
Secondary database modelsRelational DBMSTime Series DBMS infousing the Manticore Columnar LibraryDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score0.29
Rank#302  Overall
#21  Search engines
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score89.10
Rank#14  Overall
#2  Search engines
Websitecratedb.comwww.exasol.commanticoresearch.comazure.microsoft.com/­services/­data-explorerwww.splunk.com
Technical documentationcratedb.com/­docswww.exasol.com/­resourcesmanual.manticoresearch.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.splunk.com/­Documentation/­Splunk
DeveloperCrateExasolManticore SoftwareMicrosoftSplunk Inc.
Initial release20132000201720192003
Current release6.0, February 2023cloud service with continuous releases
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoGPL version 2commercialcommercial infoLimited free edition and free developer edition available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
macOS
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesFixed schemaFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonoCan index from XMLyesyes
Secondary indexesyesyesyes infofull-text index on all search fieldsall fields are automatically indexedyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesSQL-like query languageKusto Query Language (KQL), SQL subsetno infoSplunk Search Processing Language for search commands
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP REST
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
Java
Lua
Python
R
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
JavaScript
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)user defined functionsuser defined functionsYes, possible languages: KQL, Python, Ryes
Triggersnoyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSynchronous replication based on Galera libraryyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDyes infoisolated transactions for atomic changes and binary logging for safe writesnono infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlrights management via user accountsAccess rights for users, groups and roles according to SQL-standardnoAzure Active Directory AuthenticationAccess rights for users and roles
More information provided by the system vendor
CrateDBEXASOLManticore SearchMicrosoft Azure Data ExplorerSplunk
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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CrateDBEXASOLManticore SearchMicrosoft Azure Data ExplorerSplunk
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