DBMS > Altibase vs. Amazon DynamoDB vs. Faircom DB vs. Trino vs. VictoriaMetrics

System Properties Comparison Altibase vs. Amazon DynamoDB vs. Faircom DB vs. Trino vs. VictoriaMetrics

Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Fast distributed SQL query engine for big data analytics. Forked from Presto and originally named PrestoSQL

A fast, cost-effective and scalable Time Series DBMS and monitoring solution

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store
Relational DBMS

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Key-value store
Spatial DBMS
Search engine
Time Series DBMS
Wide column store

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

Score	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	4.99
Rank	#65	Overall
	#36	Relational DBMS

Score	1.23
Rank	#172	Overall
	#15	Time Series DBMS

Website

altibase.com

aws.amazon.com/dynamodb

www.faircom.com/products/faircom-db

trino.io

victoriametrics.com

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

docs.aws.amazon.com/dynamodb

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

trino.io/broadcast
trino.io/docs/current

docs.victoriametrics.com
github.com/VictoriaMetrics/VictoriaMetrics/wiki

Social network pages

Developer

Altibase

Amazon

FairCom Corporation

Trino Software Foundation

VictoriaMetrics

Initial release

1999

2012

1979

2012

2020 rebranded from PrestoSQL

2018

Current release

v7.3, 2023, August 2023

V12, November 2020

v1.91, May 2023

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

commercial

free tier for a limited amount of database operations

commercial

Restricted, free version available

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Starburst Galaxy offers a feature-rich user interface to connect all your data sources, manage your Trino clusters, and query your data.

Implementation language

C++

ANSI C, C++

Java

Server operating systems

AIX
HP-UX
Linux

hosted

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
macOS

for devlopment

FreeBSD
Linux
macOS
OpenBSD

Data scheme

yes

schema-free

schema free, schema optional, schema required, partial schema,

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

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

depending on connected data-source

SQL

Support of SQL

ANSI SQL-92

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

RESTful HTTP API

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JDBC
RESTful HTTP API
Trino CLI

Graphite protocol
InfluxDB Line Protocol
OpenTSDB
Prometheus Query API
Prometheus Remote Read/Write

Supported programming languages

C
C++
Java

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Go
Java
JavaScript (Node.js)
Python
R
Ruby

Server-side scripts

Stored procedures

stored procedures and stored functions

yes

.Net, JavaScript, C/C++

yes, depending on connected data-source

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

depending on connected data-source

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

depending on connected data-source

Synchronous replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

depending on connected data-source

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

tunable from ACID to Eventually Consistent

depending on connected data-source

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

depending on connected data-source

yes

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Fine grained access rights according to SQL-standard with additional protections for files

SQL standard access control

More information provided by the system vendor

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