DBMS > Microsoft SQL Server vs. Oracle Coherence vs. Solr vs. TerminusDB vs. VelocityDB

System Properties Comparison Microsoft SQL Server vs. Oracle Coherence vs. Solr vs. TerminusDB vs. VelocityDB

Editorial information provided by DB-Engines

Name

Description

Microsofts flagship relational DBMS

Oracles in-memory data grid solution

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Graph DBMS
Object oriented DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Spatial DBMS

Document store
RDF store

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

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

www.microsoft.com/en-us/sql-server

www.oracle.com/java/coherence

solr.apache.org

terminusdb.com

velocitydb.com

Technical documentation

learn.microsoft.com/en-US/sql/sql-server

docs.oracle.com/en/middleware/standalone/coherence

solr.apache.org/resources.html

terminusdb.github.io/terminusdb/#

velocitydb.com/UserGuide

Developer

Microsoft

Oracle

Apache Software Foundation

DataChemist Ltd.

VelocityDB Inc

Initial release

1989

2007

2006

2018

2011

Current release

SQL Server 2022, November 2022

14.1, August 2023

9.6.0, April 2024

11.0.0, January 2023

7.x

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

Apache Version 2

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

Prolog, Rust

Server operating systems

Linux
Windows

All OS with a Java VM

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

Linux

Any that supports .NET

Data scheme

yes

schema-free

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

Solr Parallel SQL Interface

SQL-like query language (WOQL)

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JCache
JPA
RESTful HTTP API

Java API
RESTful HTTP/JSON API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

.Net

Supported programming languages

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

.Net
C++
Java

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

JavaScript
Python

.Net

Server-side scripts

Stored procedures

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Java plugins

yes

Triggers

yes

Live Events

yes

User configurable commands triggered on index changes

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, but depending on the SQL-Server Edition

yes, with selectable consistency level

yes

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
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

configurable

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

yes

in-memory journaling

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

authentification to access the cache via certificates or http basic authentication

yes

Role-based access control

Based on Windows Authentication

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