DBMS > Cachelot.io vs. Hyprcubd vs. Ingres vs. Microsoft Azure Cosmos DB vs. Qdrant

System Properties Comparison Cachelot.io vs. Hyprcubd vs. Ingres vs. Microsoft Azure Cosmos DB vs. Qdrant

Editorial information provided by DB-Engines

Name

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

Description

In-memory caching system

Serverless Time Series DBMS

Well established RDBMS

Globally distributed, horizontally scalable, multi-model database service

A high-performance vector database with neural network or semantic-based matching

Primary database model

Key-value store

Time Series DBMS

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Vector DBMS

Secondary database models

Spatial DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.16
Rank	#175	Overall
	#6	Vector DBMS

Website

cachelot.io

hyprcubd.com (offline)

www.actian.com/databases/ingres

azure.microsoft.com/services/cosmos-db

github.com/qdrant/qdrant
qdrant.tech

Technical documentation

docs.actian.com/ingres

learn.microsoft.com/azure/cosmos-db

qdrant.tech/documentation

Developer

Hyprcubd, Inc.

Actian Corporation

Microsoft

Qdrant

Initial release

2015

1974

originally developed at University Berkely in early 1970s

2014

2021

Current release

11.2, May 2022

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

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.

Implementation language

C++

Rust

Server operating systems

FreeBSD
Linux
OS X

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

hosted

Docker
Linux
macOS
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

JSON types

Numbers, Strings, Geo, Boolean

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

All properties auto-indexed by default

yes

Keywords, numberic ranges, geo, full-text

SQL

Support of SQL

SQL-like query language

yes

SQL-like query language

APIs and other access methods

Memcached protocol

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

gRPC
OpenAPI 3.0
RESTful HTTP/JSON API

OpenAPI 3.0

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
Go
Java
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Ingres Replicator

yes

Implicit feature of the cloud service

Collection-level replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency, tunable consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

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

token access

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Key-based authentication

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