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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Interbase vs. Splice Machine vs. Tigris

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Interbase vs. Splice Machine vs. Tigris

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonInterbase  Xexclude from comparisonSplice Machine  Xexclude from comparisonTigris  Xexclude from comparison
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.Light-weight proven RDBMS infooriginally from BorlandOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSRelational DBMSDocument store
Key-value store
Search engine
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score4.08
Rank#75  Overall
#41  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablewww.embarcadero.com/­products/­interbasesplicemachine.comwww.tigrisdata.com
Technical documentationcloud.google.com/­bigtable/­docsdocs.embarcadero.com/­products/­interbasesplicemachine.com/­how-it-workswww.tigrisdata.com/­docs
DeveloperEsgynGoogleEmbarcaderoSplice MachineTigris Data, Inc.
Initial release20152015198420142022
Current releaseInterBase 2020, December 20193.1, March 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license availableOpen 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++, JavaCJava
Server operating systemsLinuxhostedAndroid
iOS
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeyesschema-freeyesyesyes
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.nonono infoexport as XML data possibleno
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLyesnoyesyesno
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
CLI Client
gRPC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes infoInterbase procedure and trigger languageyes infoJavano
Triggersnonoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneShared Nothhing Auto-Sharding, Columnar PartitioningSharding
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 zonesInterbase Change ViewsMulti-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesnoYes, via Full Spark Integration
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 ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMultiversion concurreny controlyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes
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)fine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAccess rights for users and roles

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More resources
EsgynDBGoogle Cloud BigtableInterbaseSplice MachineTigris
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