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DBMS > GBase vs. HarperDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sphinx

System Properties Comparison GBase vs. HarperDB vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Sphinx

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonHarperDB  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.A widely adopted in-memory data gridFully managed big data interactive analytics platformOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSDocument storeKey-value storeRelational DBMS infocolumn orientedSearch engine
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
Score0.55
Rank#248  Overall
#38  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.gbase.cnwww.harperdb.iohazelcast.comazure.microsoft.com/­services/­data-explorersphinxsearch.com
Technical documentationdocs.harperdb.io/­docshazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorersphinxsearch.com/­docs
DeveloperGeneral Data Technology Co., Ltd.HarperDBHazelcastMicrosoftSphinx Technologies Inc.
Initial release20042017200820192001
Current releaseGBase 8a, GBase 8s, GBase 8c3.1, August 20215.3.6, November 2023cloud service with continuous releases3.5.1, February 2023
License infoCommercial or Open Sourcecommercialcommercial infofree community edition availableOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoGPL version 2, commercial licence 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.
Implementation languageC, Java, PythonNode.jsJavaC++
Server operating systemsLinuxLinux
OS X
All OS with a Java VMhostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesdynamic schemaschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infoJSON data typesyesyes 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.yesnoyes infothe object must implement a serialization strategyyes
Secondary indexesyesyesyesall fields are automatically indexedyes infofull-text index on all search fields
SQL infoSupport of SQLStandard with numerous extensionsSQL-like data manipulation statementsSQL-like query languageKusto Query Language (KQL), SQL subsetSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
C API
JDBC
ODBC
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary protocol
Supported programming languagesC#.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsCustom Functions infosince release 3.1yes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Rno
Triggersyesnoyes infoEventsyes 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 partitioningA table resides as a whole on one (or more) nodes in a clusterShardingSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infothe nodes on which a table resides can be definedyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsone or two-phase-commit; repeatable reads; read commitednono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyesAccess rights for users and rolesRole-based access controlAzure Active Directory Authenticationno

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More resources
GBaseHarperDBHazelcastMicrosoft Azure Data ExplorerSphinx
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