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DBMS > EsgynDB vs. GigaSpaces vs. Google Cloud Bigtable vs. HarperDB

System Properties Comparison EsgynDB vs. GigaSpaces vs. Google Cloud Bigtable vs. HarperDB

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.
Primary database modelRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Key-value store
Wide column store
Document store
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.55
Rank#248  Overall
#38  Document stores
Websitewww.esgyn.cnwww.gigaspaces.comcloud.google.com/­bigtablewww.harperdb.io
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docs
DeveloperEsgynGigaspaces TechnologiesGoogleHarperDB
Initial release2015200020152017
Current release15.5, September 20203.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availablecommercialcommercial infofree community edition available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaJava, C++, .NetNode.js
Server operating systemsLinuxLinux
macOS
Solaris
Windows
hostedLinux
OS X
Data schemeyesschema-freeschema-freedynamic schema
Typing infopredefined data types such as float or dateyesyesnoyes infoJSON data types
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.nono infoXML can be used for describing objects metadatanono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesSQL-99 for query and DML statementsnoSQL-like data manipulation statements
APIs and other access methodsADO.NET
JDBC
ODBC
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C++
Java
Python
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Server-side scripts infoStored proceduresJava Stored ProceduresyesnoCustom Functions infosince release 3.1
Triggersnoyes, event driven architecturenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingA table resides as a whole on one (or more) nodes in a cluster
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Internal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be defined
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoMap-Reduce pattern can be built with XAP task executorsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsAtomic execution of specific operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles

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More resources
EsgynDBGigaSpacesGoogle Cloud BigtableHarperDB
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