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DBMS > EsgynDB vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. HarperDB vs. SQL.JS

System Properties Comparison EsgynDB vs. Google Cloud Bigtable vs. Google Cloud Datastore vs. HarperDB vs. SQL.JS

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHarperDB  Xexclude from comparisonSQL.JS  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformUltra-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.Port of SQLite to JavaScript
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeDocument storeRelational DBMS
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
Score4.47
Rank#76  Overall
#12  Document stores
Score0.55
Rank#248  Overall
#38  Document stores
Score0.53
Rank#252  Overall
#116  Relational DBMS
Websitewww.esgyn.cncloud.google.com/­bigtablecloud.google.com/­datastorewww.harperdb.iosql.js.org
Technical documentationcloud.google.com/­bigtable/­docscloud.google.com/­datastore/­docsdocs.harperdb.io/­docssql.js.org/­documentation/­index.html
DeveloperEsgynGoogleGoogleHarperDBAlon Zakai infoenhancements implemented by others
Initial release20152015200820172012
Current release3.1, August 2021
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infofree community edition availableOpen Source
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaNode.jsJavaScript
Server operating systemsLinuxhostedhostedLinux
OS X
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeyesschema-freeschema-freedynamic schemayes
Typing infopredefined data types such as float or dateyesnoyes, details hereyes infoJSON data typesyes
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.nonononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesnoSQL-like query language (GQL)SQL-like data manipulation statementsyes infoSQL-92 is not fully supported
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JavaScript API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.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
JavaScript
Server-side scripts infoStored proceduresJava Stored Proceduresnousing Google App EngineCustom Functions infosince release 3.1no
TriggersnonoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingA table resides as a whole on one (or more) nodes in a clusternone
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 zonesMulti-source replication using Paxosyes infothe nodes on which a table resides can be definednone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infousing Google Cloud Dataflownono
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 or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistencynone
Foreign keys infoReferential integrityyesnoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsAtomic execution of specific operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDBno infoexcept by serializing a db to a file
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyesyes
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 roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and rolesno

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More resources
EsgynDBGoogle Cloud BigtableGoogle Cloud DatastoreHarperDBSQL.JS
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