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DBMS > Faircom DB vs. GBase vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Teradata

System Properties Comparison Faircom DB vs. GBase vs. Hazelcast vs. Microsoft Azure Data Explorer vs. Teradata

Editorial information provided by DB-Engines
NameFaircom DB infoformerly c-treeACE  Xexclude from comparisonGBase  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.A widely adopted in-memory data gridFully managed big data interactive analytics platformA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelKey-value store
Relational DBMS
Relational DBMSKey-value storeRelational DBMS infocolumn orientedRelational 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
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score5.97
Rank#57  Overall
#6  Key-value stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitewww.faircom.com/­products/­faircom-dbwww.gbase.cnhazelcast.comazure.microsoft.com/­services/­data-explorerwww.teradata.com
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlhazelcast.org/­imdg/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.teradata.com
DeveloperFairCom CorporationGeneral Data Technology Co., Ltd.HazelcastMicrosoftTeradata
Initial release19792004200820191984
Current releaseV12, November 2020GBase 8a, GBase 8s, GBase 8c5.3.6, November 2023cloud service with continuous releasesTeradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open Sourcecommercial infoRestricted, free version availablecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial
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 languageANSI C, C++C, Java, PythonJava
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxAll OS with a Java VMhostedhosted
Linux
Data schemeschema free, schema optional, schema required, partial schema,yesschema-freeFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes 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.noyesyes infothe object must implement a serialization strategyyesyes
Secondary indexesyesyesyesall fields are automatically indexedyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyes, ANSI SQL with proprietary extensionsStandard with numerous extensionsSQL-like query languageKusto Query Language (KQL), SQL subsetyes infoSQL 2016 + extensions
APIs and other access methodsADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
C API
JDBC
ODBC
JCache
JPA
Memcached protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languages.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresyes info.Net, JavaScript, C/C++user defined functionsyes infoEvent Listeners, Executor ServicesYes, possible languages: KQL, Python, Ryes infoUDFs, stored procedures, table functions in parallel
Triggersyesyesyes infoEventsyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes
Partitioning methods infoMethods for storing different data on different nodesFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioninghorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding infoImplicit feature of the cloud serviceSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).yesyes infoReplicated Mapyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
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 systemEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datatunable from ACID to Eventually ConsistentACIDone or two-phase-commit; repeatable reads; read commitednoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentYes, tunable from durable to delayed durability to in-memoryyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlFine grained access rights according to SQL-standard with additional protections for filesyesRole-based access controlAzure Active Directory Authenticationfine grained access rights according to SQL-standard

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More resources
Faircom DB infoformerly c-treeACEGBaseHazelcastMicrosoft Azure Data ExplorerTeradata
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