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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Hive vs. InterSystems Caché vs. VictoriaMetrics

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Hive vs. InterSystems Caché vs. VictoriaMetrics

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonVictoriaMetrics  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.data warehouse software for querying and managing large distributed datasets, built on HadoopA multi-model DBMS and application serverA fast, cost-effective and scalable Time Series DBMS and monitoring solution
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Time Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.26
Rank#311  Overall
#141  Relational DBMS
Score3.86
Rank#90  Overall
#13  Key-value stores
#7  Wide column stores
Score64.82
Rank#18  Overall
#12  Relational DBMS
Score1.59
Rank#162  Overall
#14  Time Series DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablehive.apache.orgwww.intersystems.com/­products/­cachevictoriametrics.com
Technical documentationcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homedocs.intersystems.comdocs.victoriametrics.com
github.com/­VictoriaMetrics/­VictoriaMetrics/­wiki
DeveloperEsgynGoogleApache Software Foundation infoinitially developed by FacebookInterSystemsVictoriaMetrics
Initial release20152015201219972018
Current release3.1.3, April 20222018.1.4, May 2020v1.91, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2commercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJavaGo
Server operating systemsLinuxhostedAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
FreeBSD
Linux
macOS
OpenBSD
Data schemeyesschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyesno
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsyesno
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
.NET Client API
JDBC
ODBC
RESTful HTTP API
Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
C#
C++
Java
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes infouser defined functions and integration of map-reduceyesno
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnone
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 zonesselectable replication factorSource-replica replicationSynchronous replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACIDno
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.nonoyesno
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 rolesAccess rights for users, groups and roles

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More resources
EsgynDBGoogle Cloud BigtableHiveInterSystems CachéVictoriaMetrics
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