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DBMS > eXtremeDB vs. LevelDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. RocksDB

System Properties Comparison eXtremeDB vs. LevelDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. RocksDB

Editorial information provided by DB-Engines
NameeXtremeDB  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRocksDB  Xexclude from comparison
DescriptionNatively in-memory DBMS with options for persistency, high-availability and clusteringEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesGlobally distributed, horizontally scalable, multi-model database serviceFully managed big data interactive analytics platformEmbeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelRelational DBMS
Time Series DBMS
Key-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS infocolumn orientedKey-value store
Secondary database modelsSpatial DBMSDocument 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
Score0.80
Rank#214  Overall
#99  Relational DBMS
#18  Time Series DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Score27.71
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score3.41
Rank#86  Overall
#11  Key-value stores
Websitewww.mcobject.comgithub.com/­google/­leveldbazure.microsoft.com/­services/­cosmos-dbazure.microsoft.com/­services/­data-explorerrocksdb.org
Technical documentationwww.mcobject.com/­docs/­extremedb.htmgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdlearn.microsoft.com/­azure/­cosmos-dbdocs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­facebook/­rocksdb/­wiki
DeveloperMcObjectGoogleMicrosoftMicrosoftFacebook, Inc.
Initial release20012011201420192013
Current release8.2, 20211.23, February 2021cloud service with continuous releases9.2.1, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoBSDcommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++C++
Server operating systemsAIX
HP-UX
Linux
macOS
Solaris
Windows
Illumos
Linux
OS X
Windows
hostedhostedLinux
Data schemeyesschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesnoyes infoJSON typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.no infosupport of XML interfaces availablenoyesno
Secondary indexesyesnoyes infoAll properties auto-indexed by defaultall fields are automatically indexedno
SQL infoSupport of SQLyes infowith the option: eXtremeSQLnoSQL-like query languageKusto Query Language (KQL), SQL subsetno
APIs and other access methods.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API
DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
C++ API
Java API
Supported programming languages.Net
C
C#
C++
Java
Lua
Python
Scala
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresyesnoJavaScriptYes, possible languages: KQL, Python, Rno
Triggersyes infoby defining eventsnoJavaScriptyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning / shardingnoneSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesActive Replication Fabric™ for IoT
Multi-source replication infoby means of eXtremeDB Cluster option
Source-replica replication infoby means of eXtremeDB High Availability option
noneyes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*Spark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoMulti-item ACID transactions with snapshot isolation within a partitionnoyes
Concurrency infoSupport for concurrent manipulation of datayes infoOptimistic (MVCC) and pessimistic (locking) strategies availableyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith automatic compression on writesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnoAccess rights can be defined down to the item levelAzure Active Directory Authenticationno
More information provided by the system vendor
eXtremeDBLevelDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBMicrosoft Azure Data ExplorerRocksDB
Specific characteristicseXtremeDB is an in-memory and/or persistent database system that offers an ultra-small...
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Competitive advantageseXtremeDB databases can be modeled relationally or as objects and can utilize SQL...
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Typical application scenariosIoT application across all markets: Industrial Control, Netcom, Telecom, Defense,...
» more
Key customersSchneider Electronics, F5 Networks, TNS, Boeing, Northrop Grumman, GoPro, ViaSat,...
» more
Market metricsWith hundreds of customers and over 30 million devices/applications using the product...
» more
Licensing and pricing modelsFor server use cases, there is a simple per-server license irrespective of the number...
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
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Speedb: A high performance RocksDB-compliant key-value store optimized for write-intensive workloads.
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More resources
eXtremeDBLevelDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBMicrosoft Azure Data ExplorerRocksDB
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