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DBMS > GBase vs. Ignite vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. TimescaleDB

System Properties Comparison GBase vs. Ignite vs. Microsoft Azure Data Explorer vs. Sadas Engine vs. TimescaleDB

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSadas Engine  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMS infocolumn orientedRelational DBMSTime Series DBMS
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
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websitewww.gbase.cnignite.apache.orgazure.microsoft.com/­services/­data-explorerwww.sadasengine.comwww.timescale.com
Technical documentationapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationdocs.timescale.com
DeveloperGeneral Data Technology Co., Ltd.Apache Software FoundationMicrosoftSADAS s.r.l.Timescale
Initial release20042015201920062017
Current releaseGBase 8a, GBase 8s, GBase 8cApache Ignite 2.6cloud service with continuous releases8.02.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial infofree trial version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, Java, PythonC++, Java, .NetC++C
Server operating systemsLinuxLinux
OS X
Solaris
Windows
hostedAIX
Linux
Windows
Linux
OS X
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesyesyesnoyes
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLStandard with numerous extensionsANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
C API
JDBC
ODBC
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#C#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, Rnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesyes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlyesSecurity Hooks for custom implementationsAzure Active Directory AuthenticationAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
GBaseIgniteMicrosoft Azure Data ExplorerSadas EngineTimescaleDB
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