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DBMS > Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics vs. Teradata

System Properties Comparison Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics vs. Teradata

Editorial information provided by DB-Engines
NameDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionDistributed and scalable native Graph DBMSEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelGraph DBMSRelational DBMSKey-value store
Wide column store
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.53
Rank#152  Overall
#15  Graph DBMS
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitedgraph.iowww.esgyn.cncloud.google.com/­bigtableazure.microsoft.com/­services/­synapse-analyticswww.teradata.com
Technical documentationdgraph.io/­docscloud.google.com/­bigtable/­docsdocs.microsoft.com/­azure/­synapse-analyticsdocs.teradata.com
DeveloperDgraph Labs, Inc.EsgynGoogleMicrosoftTeradata
Initial release20162015201520161984
Current releaseTeradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++, JavaC++
Server operating systemsLinux
OS X
Windows
Linuxhostedhostedhosted
Linux
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesyes
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.nonononoyes
Secondary indexesyesyesnoyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLnoyesnoyesyes infoSQL 2016 + extensions
APIs and other access methodsGraphQL query language
gRPC (using protocol buffers) API
HTTP API
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C#
Java
PHP
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnoJava Stored ProceduresnoTransact SQLyes infoUDFs, stored procedures, table functions in parallel
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesyesShardingShardingSharding, horizontal partitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSynchronous replication via RaftMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono 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 dataACIDACIDAtomic single-row operationsACIDACID
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.nonoyes
User concepts infoAccess controlno infoPlanned for future releasesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yesfine grained access rights according to SQL-standard

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More resources
DgraphEsgynDBGoogle Cloud BigtableMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTeradata
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