DBMS > Hazelcast vs. Hyprcubd vs. PostgreSQL vs. Tarantool

System Properties Comparison Hazelcast vs. Hyprcubd vs. PostgreSQL vs. Tarantool

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Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

A widely adopted in-memory data grid

Serverless Time Series DBMS

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

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

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Document store
Key-value store
Relational DBMS

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

Spatial DBMS

with Tarantool/GIS extension

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	1.72
Rank	#144	Overall
	#25	Document stores
	#25	Key-value stores
	#66	Relational DBMS

Website

hazelcast.com

hyprcubd.com (offline)

www.postgresql.org

www.tarantool.io

Technical documentation

hazelcast.org/imdg/docs

www.postgresql.org/docs

www.tarantool.io/en/doc

Developer

Hazelcast

Hyprcubd, Inc.

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2008

1989

1989: Postgres, 1996: PostgreSQL

2008

Current release

5.3.6, November 2023

16.3, May 2024

2.10.0, May 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

BSD

Open Source

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

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM

hosted

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

BSD
Linux
macOS

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

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

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.

yes

the object must implement a serialization strategy

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

standard with numerous extensions

Full-featured ANSI SQL support

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

gRPC (https)

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

Open binary protocol

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Server-side scripts

Stored procedures

yes

Event Listeners, Executor Services

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Lua, C and SQL stored procedures

Triggers

yes

Events

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and (since PostgreSQL 11) by hash

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

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

Source-replica replication

other methods possible by using 3rd party extensions

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

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

one or two-phase-commit; repeatable reads; read commited

ACID

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

yes, cooperative multitasking

Durability

Support for making data persistent

yes

yes, write ahead logging

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

User concepts

Access control

Role-based access control

token access

fine grained access rights according to SQL-standard

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

More information provided by the system vendor

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