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DBMS > EsgynDB vs. Fujitsu Enterprise Postgres vs. Ingres vs. Tarantool

System Properties Comparison EsgynDB vs. Fujitsu Enterprise Postgres vs. Ingres vs. Tarantool

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Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonIngres  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.Well established RDBMSIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.25
Rank#312  Overall
#138  Relational DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.esgyn.cnwww.postgresql.fastware.comwww.actian.com/­databases/­ingreswww.tarantool.io
Technical documentationwww.postgresql.fastware.com/­product-manualsdocs.actian.com/­ingreswww.tarantool.io/­en/­doc
DeveloperEsgynPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyActian CorporationVK
Initial release20151974 infooriginally developed at University Berkely in early 1970s2008
Current releaseFujitsu Enterprise Postgres 14, January 202211.2, May 20222.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++, JavaCCC and C++
Server operating systemsLinuxLinux
Windows
AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
BSD
Linux
macOS
Data schemeyesyesyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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 infobut tools for importing/exporting data from/to XML-files availableno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLyesyesyesFull-featured ANSI SQL support
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Open binary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.Net.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresJava Stored Proceduresuser defined functionsyesLua, C and SQL stored procedures
Triggersnoyesyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and by hashhorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersSource-replica replicationIngres ReplicatorAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyesyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yes infoMVCCyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
EsgynDBFujitsu Enterprise PostgresIngresTarantool
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Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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