DBMS > JaguarDB vs. Quasardb vs. RavenDB vs. Vertica

System Properties Comparison JaguarDB vs. Quasardb vs. RavenDB vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

Distributed, high-performance timeseries database

Open Source Operational and Transactional Enterprise NoSQL Document Database

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Key-value store
Vector DBMS

Time Series DBMS

Document store

Relational DBMS

Column oriented

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

Spatial DBMS
Time Series DBMS

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

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

Technical documentation

www.jaguardb.com/support.html

doc.quasar.ai/master

ravendb.net/docs

vertica.com/documentation

Developer

DataJaguar, Inc.

quasardb

Hibernating Rhinos

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2015

2009

2010

2005

Current release

3.3 July 2023

3.14.1, January 2024

5.4, July 2022

12.0.3, January 2023

License

Commercial or Open Source

Open Source

GPL V3.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

AGPL version 3, commercial license available

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux

BSD
Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

Linux

Data scheme

yes

schema-free

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

SQL-like query language (RQL)

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC

HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

consistent hashing

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication with selectable replication factor

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

rights management via user accounts

Cryptographically strong user authentication and audit trail

Authorization levels configured per client per database

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

Specific characteristics

Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more

Competitive advantages

Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more

Typical application scenarios

Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more

Key customers

Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more

Licensing and pricing models

Cost-based models and subscription-based models are both available. One license is...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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