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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Google Cloud Spanner vs. HugeGraph vs. InterSystems Caché

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Google Cloud Spanner vs. HugeGraph vs. InterSystems Caché

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonHugeGraph  Xexclude from comparisonInterSystems Caché  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionEnterprise-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.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A fast-speed and highly-scalable Graph DBMSA multi-model DBMS and application server
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSGraph DBMSKey-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablecloud.google.com/­spannergithub.com/­hugegraph
hugegraph.apache.org
www.intersystems.com/­products/­cache
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­spanner/­docshugegraph.apache.org/­docsdocs.intersystems.com
DeveloperEsgynGoogleGoogleBaiduInterSystems
Initial release20152015201720181997
Current release0.92018.1.4, May 2020
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2.0commercial
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++, JavaJava
Server operating systemsLinuxhostedhostedLinux
macOS
Unix
AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyesdepending on used data model
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.nonononoyes
Secondary indexesyesnoyesyes infoalso supports composite index and range indexyes
SQL infoSupport of SQLyesnoyes infoQuery statements complying to ANSI 2011noyes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Java API
RESTful HTTP API
TinkerPop Gremlin
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
Go
Java
JavaScript (Node.js)
Python
Groovy
Java
Python
C#
C++
Java
Server-side scripts infoStored proceduresJava Stored Proceduresnonoasynchronous Gremlin script jobsyes
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes infodepending on used storage backend, e.g. Cassandra and HBasenone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication with 3 replicas for regional instances.yes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infousing Google Cloud Dataflowvia hugegraph-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyes infoedges in graphyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoStrict serializable isolationACIDACID
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.nononoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users, roles and permissionsAccess rights for users, groups and roles

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More resources
EsgynDBGoogle Cloud BigtableGoogle Cloud SpannerHugeGraphInterSystems Caché
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