DBMS > Fujitsu Enterprise Postgres vs. Oracle Coherence vs. Tarantool vs. Warp 10

System Properties Comparison Fujitsu Enterprise Postgres vs. Oracle Coherence vs. Tarantool vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Oracles in-memory data grid solution

In-memory computing platform with a flexible data schema for efficiently building high-performance applications

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Key-value store

Document store
Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

with Tarantool/GIS extension

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	1.67
Rank	#143	Overall
	#25	Document stores
	#25	Key-value stores
	#65	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

www.postgresql.fastware.com

www.oracle.com/java/coherence

www.tarantool.io

www.warp10.io

Technical documentation

www.postgresql.fastware.com/product-manuals

docs.oracle.com/en/middleware/standalone/coherence

www.tarantool.io/en/doc

www.warp10.io/content/02_Getting_started

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Oracle

SenX

Initial release

2007

2008

2015

Current release

Fujitsu Enterprise Postgres 14, January 2022

14.1, August 2023

2.10.0, May 2022

License

Commercial or Open Source

commercial

Open Source

BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C and C++

Java

Server operating systems

Linux
Windows

All OS with a Java VM

BSD
Linux
macOS

Linux
OS X
Windows

Data scheme

yes

schema-free

Flexible data schema: relational definition for tables with ability to store json-like documents in columns

schema-free

Typing

predefined data types such as float or date

yes

string, double, decimal, uuid, integer, blob, boolean, datetime

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

Full-featured ANSI SQL support

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JCache
JPA
RESTful HTTP API

Open binary protocol

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C++
Java

C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust

Server-side scripts

Stored procedures

user defined functions

Lua, C and SQL stored procedures

yes

WarpScript

Triggers

yes

Live Events

yes, before/after data modification events, on replication events, client session events

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

Sharding

Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, with selectable consistency level

Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Casual consistency across sharding partitions
Eventual consistency within replicaset partition

when using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition

when using Raft

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

configurable

ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

yes, cooperative multitasking

yes

Durability

Support for making data persistent

yes

optionally

yes, write ahead logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, full featured in-memory storage engine with persistence

yes

User concepts

Access control

fine grained access rights according to SQL-standard

authentification to access the cache via certificates or http basic authentication

Access Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

DB-Engines blog posts

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

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