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DBMS > LevelDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. RDF4J vs. RocksDB

System Properties Comparison LevelDB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Data Explorer vs. RDF4J vs. RocksDB

Editorial information provided by DB-Engines
NameLevelDB  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonRocksDB  Xexclude from comparison
DescriptionEmbeddable 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 platformRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Embeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelKey-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS infocolumn orientedRDF storeKey-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
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
Score0.74
Rank#222  Overall
#9  RDF stores
Score3.41
Rank#86  Overall
#11  Key-value stores
Websitegithub.com/­google/­leveldbazure.microsoft.com/­services/­cosmos-dbazure.microsoft.com/­services/­data-explorerrdf4j.orgrocksdb.org
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdlearn.microsoft.com/­azure/­cosmos-dbdocs.microsoft.com/­en-us/­azure/­data-explorerrdf4j.org/­documentationgithub.com/­facebook/­rocksdb/­wiki
DeveloperGoogleMicrosoftMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Facebook, Inc.
Initial release20112014201920042013
Current release1.23, February 2021cloud service with continuous releases9.2.1, May 2024
License infoCommercial or Open SourceOpen Source infoBSDcommercialcommercialOpen Source infoEclipse Distribution License (EDL), v1.0.Open Source infoBSD
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaC++
Server operating systemsIllumos
Linux
OS X
Windows
hostedhostedLinux
OS X
Unix
Windows
Linux
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yes infoRDF Schemasschema-free
Typing infopredefined data types such as float or datenoyes infoJSON typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesno
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.noyesno
Secondary indexesnoyes infoAll properties auto-indexed by defaultall fields are automatically indexedyesno
SQL infoSupport of SQLnoSQL-like query languageKusto Query Language (KQL), SQL subsetnono
APIs and other access methodsDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
C++ API
Java API
Supported programming languagesC++
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
Java
PHP
Python
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresnoJavaScriptYes, possible languages: KQL, Python, Ryesno
TriggersnoJavaScriptyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding infoImplicit feature of the cloud servicenonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoImplicit feature of the cloud serviceyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*Spark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoMulti-item ACID transactions with snapshot isolation within a partitionnoACID infoIsolation support depends on the API usedyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyes infowith automatic compression on writesyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlnoAccess rights can be defined down to the item levelAzure Active Directory Authenticationnono

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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
LevelDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBMicrosoft Azure Data ExplorerRDF4J infoformerly known as SesameRocksDB
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