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DBMS > etcd vs. HugeGraph vs. Microsoft Azure Data Explorer vs. RocksDB

System Properties Comparison etcd vs. HugeGraph vs. Microsoft Azure Data Explorer vs. RocksDB

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonHugeGraph  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRocksDB  Xexclude from comparison
DescriptionA distributed reliable key-value storeA fast-speed and highly-scalable Graph DBMSFully managed big data interactive analytics platformEmbeddable persistent key-value store optimized for fast storage (flash and RAM)
Primary database modelKey-value storeGraph DBMSRelational DBMS infocolumn orientedKey-value store
Secondary database modelsDocument 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
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score3.65
Rank#85  Overall
#11  Key-value stores
Websiteetcd.io
github.com/­etcd-io/­etcd
github.com/­hugegraph
hugegraph.apache.org
azure.microsoft.com/­services/­data-explorerrocksdb.org
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hugegraph.apache.org/­docsdocs.microsoft.com/­en-us/­azure/­data-explorergithub.com/­facebook/­rocksdb/­wiki
DeveloperBaiduMicrosoftFacebook, Inc.
Initial release201820192013
Current release3.4, August 20190.9cloud service with continuous releases8.11.4, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoJavaC++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
macOS
Unix
hostedLinux
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or datenoyesyes 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.nonoyesno
Secondary indexesnoyes infoalso supports composite index and range indexall fields are automatically indexedno
SQL infoSupport of SQLnonoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsgRPC
JSON over HTTP
Java API
RESTful HTTP API
TinkerPop Gremlin
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
C++ API
Java API
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Groovy
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Go
Java
Perl
Python
Ruby
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsYes, possible languages: KQL, Python, Rno
Triggersyes, watching key changesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infodepending on used storage backend, e.g. Cassandra and HBaseyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparkSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoyes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlnoUsers, roles and permissionsAzure Active Directory Authenticationno

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etcdHugeGraphMicrosoft Azure Data ExplorerRocksDB
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