DBMS > Graph Engine vs. OpenMLDB vs. Solr

System Properties Comparison Graph Engine vs. OpenMLDB vs. Solr

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

An open-source machine learning database that provides a feature platform for training and inference

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

Primary database model

Graph DBMS
Key-value store

Time Series DBMS

Search engine

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.02
Rank	#367	Overall
	#37	Time Series DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.graphengine.io

openmldb.ai

solr.apache.org

Technical documentation

www.graphengine.io/docs/manual

openmldb.ai/docs/zh/main

solr.apache.org/resources.html

Developer

Microsoft

4 Paradigm Inc.

Apache Software Foundation

Initial release

2010

2020

2006

Current release

2024-2 February 2024

9.6.0, April 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache Version 2

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

.NET and C

C++, Java, Scala

Java

Server operating systems

.NET

Linux

All OS with a Java VM

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

Data scheme

yes

Fixed schema

yes

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

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

SQL

Support of SQL

yes

Solr Parallel SQL Interface

APIs and other access methods

RESTful HTTP API

JDBC
SQLAlchemy

Java API
RESTful HTTP/JSON API

Supported programming languages

C#
C++
F#
Visual Basic

C++
Go
Java
Python
Scala

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

Server-side scripts

Stored procedures

yes

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

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

Foreign keys

Referential integrity

Transaction concepts

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

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

yes

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More resources

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