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DBMS > GBase vs. Hazelcast vs. KeyDB vs. Microsoft Azure Data Explorer vs. Tigris

System Properties Comparison GBase vs. Hazelcast vs. KeyDB vs. Microsoft Azure Data Explorer vs. Tigris

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonHazelcast  Xexclude from comparisonKeyDB  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTigris  Xexclude from comparison
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A widely adopted in-memory data gridAn ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocolsFully managed big data interactive analytics platformA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMSKey-value storeKey-value storeRelational DBMS infocolumn orientedDocument store
Key-value store
Search engine
Time Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Document 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
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.71
Rank#226  Overall
#33  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.02
Rank#369  Overall
#51  Document stores
#55  Key-value stores
#24  Search engines
#38  Time Series DBMS
Websitewww.gbase.cnhazelcast.comgithub.com/­Snapchat/­KeyDB
keydb.dev
azure.microsoft.com/­services/­data-explorerwww.tigrisdata.com
Technical documentationhazelcast.org/­imdg/­docsdocs.keydb.devdocs.microsoft.com/­en-us/­azure/­data-explorerwww.tigrisdata.com/­docs
DeveloperGeneral Data Technology Co., Ltd.HazelcastEQ Alpha Technology Ltd.MicrosoftTigris Data, Inc.
Initial release20042008201920192022
Current releaseGBase 8a, GBase 8s, GBase 8c5.3.6, November 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoBSD-3commercialOpen Source infoApache Version 2.0
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.
Implementation languageC, Java, PythonJavaC++
Server operating systemsLinuxAll OS with a Java VMLinuxhostedLinux
macOS
Windows
Data schemeyesschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyespartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexesyes 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.yesyes infothe object must implement a serialization strategynoyesno
Secondary indexesyesyesyes infoby using the Redis Search moduleall fields are automatically indexedyes
SQL infoSupport of SQLStandard with numerous extensionsSQL-like query languagenoKusto Query Language (KQL), SQL subsetno
APIs and other access methodsADO.NET
C API
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
Proprietary protocol infoRESP - REdis Serialization ProtocoMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
CLI Client
gRPC
RESTful HTTP API
Supported programming languagesC#.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresuser defined functionsyes infoEvent Listeners, Executor ServicesLuaYes, possible languages: KQL, Python, Rno
Triggersyesyes infoEventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated MapMulti-source replication
Source-replica replication
yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Strong eventual consistency with CRDTs
Eventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedOptimistic locking, atomic execution of commands blocks and scriptsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logsyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesRole-based access controlsimple password-based access control and ACLAzure Active Directory AuthenticationAccess rights for users and roles

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More resources
GBaseHazelcastKeyDBMicrosoft Azure Data ExplorerTigris
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