DBMS > Blueflood vs. Oracle vs. Solr vs. Valentina Server vs. Yaacomo

System Properties Comparison Blueflood vs. Oracle vs. Solr vs. Valentina Server vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Scalable TimeSeries DBMS based on Cassandra

Widely used RDBMS

A widely used distributed, scalable search engine based on Apache Lucene

Object-relational database and reports server

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Secondary database models

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

Spatial DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

blueflood.io

www.oracle.com/database

solr.apache.org

www.valentina-db.net

yaacomo.com

Technical documentation

github.com/rax-maas/blueflood/wiki

docs.oracle.com/en/database

solr.apache.org/resources.html

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Rackspace

Oracle

Apache Software Foundation

Paradigma Software

Q2WEB GmbH

Initial release

2013

1980

2006

1999

2009

Current release

23c, September 2023

9.6.0, April 2024

5.7.5

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

Apache Version 2

commercial

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
OS X

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

predefined scheme

yes

Schemaless in JSON and XML columns

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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.

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

Solr Parallel SQL Interface

yes

APIs and other access methods

HTTP REST

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
RESTful HTTP/JSON API

ODBC

JDBC
ODBC

Supported programming languages

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

PL/SQL

also stored procedures in Java possible

Java plugins

yes

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding, horizontal partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

yes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

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

Version 12c introduced the new option 'Oracle Database In-Memory'

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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