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

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

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHive  Xexclude from comparisonInfinityDB  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.data warehouse software for querying and managing large distributed datasets, built on HadoopA Java embedded Key-Value Store which extends the Java Map interfaceA multi-model DBMS and application server
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSKey-value storeKey-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
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Websitewww.esgyn.cncloud.google.com/­bigtablehive.apache.orgboilerbay.comwww.intersystems.com/­products/­cache
Technical documentationcloud.google.com/­bigtable/­docscwiki.apache.org/­confluence/­display/­Hive/­Homeboilerbay.com/­infinitydb/­manualdocs.intersystems.com
DeveloperEsgynGoogleApache Software Foundation infoinitially developed by FacebookBoiler Bay Inc.InterSystems
Initial release20152015201220021997
Current release3.1.3, April 20224.02018.1.4, May 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache Version 2commercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJavaJava
Server operating systemsLinuxhostedAll OS with a Java VMAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradedepending on used data model
Typing infopredefined data types such as float or dateyesnoyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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.nononoyes
Secondary indexesyesnoyesno infomanual creation possible, using inversions based on multi-value capabilityyes
SQL infoSupport of SQLyesnoSQL-like DML and DDL statementsnoyes
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Thrift
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
.NET Client API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
C++
Java
PHP
Python
JavaC#
C++
Java
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes infouser defined functions and integration of map-reducenoyes
Triggersnonononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnonenone
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 factornoneSource-replica 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 Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integrityyesnonono infomanual creation possible, using inversions based on multi-value capabilityyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsnoACID infoOptimistic locking for transactions; no isolation for bulk loadsACID
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.nononoyes
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 rolesnoAccess rights for users, groups and roles

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More resources
EsgynDBGoogle Cloud BigtableHiveInfinityDBInterSystems Caché
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