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DBMS > GBase vs. Microsoft Azure Data Explorer vs. Microsoft Azure Synapse Analytics vs. Sqrrl vs. Tarantool

System Properties Comparison GBase vs. Microsoft Azure Data Explorer vs. Microsoft Azure Synapse Analytics vs. Sqrrl vs. Tarantool

Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSqrrl  Xexclude from comparisonTarantool  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.
DescriptionWidely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.Fully managed big data interactive analytics platformElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerAdaptable, secure NoSQL built on Apache AccumuloIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSRelational DBMS infocolumn orientedRelational DBMSDocument store
Graph DBMS
Key-value store
Wide column store
Document store
Key-value store
Relational 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
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.05
Rank#186  Overall
#86  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.gbase.cnazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­services/­synapse-analyticssqrrl.comwww.tarantool.io
Technical documentationdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­azure/­synapse-analyticswww.tarantool.io/­en/­doc
DeveloperGeneral Data Technology Co., Ltd.MicrosoftMicrosoftAmazon infooriginally Sqrrl Data, Inc.VK
Initial release20042019201620122008
Current releaseGBase 8a, GBase 8s, GBase 8ccloud service with continuous releases2.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, PythonC++JavaC and C++
Server operating systemsLinuxhostedhostedLinuxBSD
Linux
macOS
Data schemeyesFixed schema with schema-less datatypes (dynamic)yesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.yesyesnono
Secondary indexesyesall fields are automatically indexedyesyesyes
SQL infoSupport of SQLStandard with numerous extensionsKusto Query Language (KQL), SQL subsetyesnoFull-featured ANSI SQL support
APIs and other access methodsADO.NET
C API
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
Open binary protocol
Supported programming languagesC#.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C#
Java
PHP
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresuser defined functionsYes, possible languages: KQL, Python, RTransact SQLnoLua, C and SQL stored procedures
Triggersyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynonoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by range, list and hash) and vertical partitioningSharding infoImplicit feature of the cloud serviceSharding, horizontal partitioningSharding infomaking use of HadoopSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesselectable replication factor infomaking use of HadoopAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Casual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyesnono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDAtomic updates per row, document, or graph entityACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlyesAzure Active Directory AuthenticationyesCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
GBaseMicrosoft Azure Data ExplorerMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSqrrlTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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