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DBMS > EsgynDB vs. Faircom DB vs. Google Cloud Datastore vs. LMDB

System Properties Comparison EsgynDB vs. Faircom DB vs. Google Cloud Datastore vs. LMDB

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonLMDB  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performant, light-weight, embedded key-value database library
Primary database modelRelational DBMSKey-value store
Relational DBMS
Document storeKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score2.09
Rank#121  Overall
#20  Key-value stores
Websitewww.esgyn.cnwww.faircom.com/­products/­faircom-dbcloud.google.com/­datastorewww.symas.com/­symas-embedded-database-lmdb
Technical documentationdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlcloud.google.com/­datastore/­docswww.lmdb.tech/­doc
DeveloperEsgynFairCom CorporationGoogleSymas
Initial release2015197920082011
Current releaseV12, November 20200.9.32, January 2024
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercialOpen Source
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaANSI C, C++C
Server operating systemsLinuxAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinux
Unix
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,schema-freeschema-free
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes, details here
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.nononono
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesyes, ANSI SQL with proprietary extensionsSQL-like query language (GQL)no
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
Server-side scripts infoStored proceduresJava Stored Proceduresyes info.Net, JavaScript, C/C++using Google App Engineno
TriggersnoyesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replication using Paxosnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
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 Consistency
Foreign keys infoReferential integrityyesyesyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes
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-standardFine grained access rights according to SQL-standard with additional protections for filesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
EsgynDBFaircom DB infoformerly c-treeACEGoogle Cloud DatastoreLMDB
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