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DBMS > GeoMesa vs. Google Cloud Bigtable vs. Kingbase vs. Microsoft Azure Synapse Analytics vs. Teradata

System Properties Comparison GeoMesa vs. Google Cloud Bigtable vs. Kingbase vs. Microsoft Azure Synapse Analytics vs. Teradata

Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKingbase  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelSpatial DBMSKey-value store
Wide column store
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#211  Overall
#4  Spatial DBMS
Score2.91
Rank#93  Overall
#15  Key-value stores
#8  Wide column stores
Score0.43
Rank#259  Overall
#119  Relational DBMS
Score18.72
Rank#31  Overall
#19  Relational DBMS
Score40.69
Rank#23  Overall
#16  Relational DBMS
Websitewww.geomesa.orgcloud.google.com/­bigtablewww.kingbase.com.cnazure.microsoft.com/­services/­synapse-analyticswww.teradata.com
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlcloud.google.com/­bigtable/­docsdocs.microsoft.com/­azure/­synapse-analyticsdocs.teradata.com
DeveloperCCRi and othersGoogleBeiJing KINGBASE Information technologies inc.MicrosoftTeradata
Initial release20142015199920161984
Current release5.0.1, July 2024V8.0, August 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC and JavaC++
Server operating systemshostedLinux
Windows
hostedhosted
Linux
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nonoyesnoyes
Secondary indexesyesnoyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnonoStandard with numerous extensionsyesyes infoSQL 2016 + extensions
APIs and other access methodsgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT
ADO.NET
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C#
Java
PHP
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnonouser defined functionsTransact SQLyes infoUDFs, stored procedures, table functions in parallel
Triggersnonoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardinghorizontal partitioning (by range, list and hash) and vertical partitioningSharding, horizontal partitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerInternal replication in Colossus, and regional replication between two clusters in different zonesyesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACIDACIDACID
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.depending on storage layernoyes
User concepts infoAccess controlyes infodepending on the DBMS used for storageAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyesfine grained access rights according to SQL-standard

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More resources
GeoMesaGoogle Cloud BigtableKingbaseMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTeradata
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