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DBMS > EsgynDB vs. Google Cloud Bigtable vs. InfinityDB vs. InterSystems Caché vs. Spark SQL

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

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInfinityDB  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSpark SQL  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 Java embedded Key-Value Store which extends the Java Map interfaceA multi-model DBMS and application serverSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value storeKey-value store
Object oriented DBMS
Relational 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
Score0.00
Rank#378  Overall
#57  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtableboilerbay.comwww.intersystems.com/­products/­cachespark.apache.org/­sql
Technical documentationcloud.google.com/­bigtable/­docsboilerbay.com/­infinitydb/­manualdocs.intersystems.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperEsgynGoogleBoiler Bay Inc.InterSystemsApache Software Foundation
Initial release20152015200219972014
Current release4.02018.1.4, May 20203.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialcommercialOpen Source infoApache 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++, JavaJavaScala
Server operating systemsLinuxhostedAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradedepending on used data modelyes
Typing infopredefined data types such as float or dateyesnoyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.nononoyesno
Secondary indexesyesnono infomanual creation possible, using inversions based on multi-value capabilityyesno
SQL infoSupport of SQLyesnonoyesSQL-like DML and DDL statements
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
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
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
JavaC#
C++
Java
Java
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored Proceduresnonoyesno
Triggersnononoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenoneyes, utilizing Spark Core
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 zonesnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnono
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 Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integrityyesnono infomanual creation possible, using inversions based on multi-value capabilityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoOptimistic locking for transactions; no isolation for bulk loadsACIDno
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.nononoyesno
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)noAccess rights for users, groups and rolesno

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More resources
EsgynDBGoogle Cloud BigtableInfinityDBInterSystems CachéSpark SQL
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