DBMS > LeanXcale vs. ObjectBox vs. Solr vs. Stardog vs. Vitess

System Properties Comparison LeanXcale vs. ObjectBox vs. Solr vs. Stardog vs. Vitess

Editorial information provided by DB-Engines

Name

Description

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

Extremely fast embedded database for small devices, IoT and Mobile

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Key-value store
Relational DBMS

Secondary database models

Time Series DBMS

Spatial DBMS

Document store
Spatial DBMS

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	1.20
Rank	#170	Overall
	#5	Object oriented DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

Technical documentation

docs.objectbox.io

solr.apache.org/resources.html

docs.stardog.com

vitess.io/docs

Developer

LeanXcale

ObjectBox Limited

Apache Software Foundation

Stardog-Union

The Linux Foundation, PlanetScale

Initial release

2015

2017

2006

2010

2013

Current release

9.6.0, April 2024

7.3.0, May 2020

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache Version 2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache Version 2.0, commercial licenses available

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

C and C++

Java

Server operating systems

Android
iOS
Linux
macOS
Windows

All OS with a Java VM

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

Linux
macOS
Windows

Docker
Linux
macOS

Data scheme

yes

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

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

yes

All search fields are automatically indexed

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

through Apache Derby

Solr Parallel SQL Interface

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

with proprietary extensions

APIs and other access methods

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

Proprietary native API

Java API
RESTful HTTP/JSON API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

C
Java
Scala

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

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

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java plugins

user defined functions and aggregates, HTTP Server extensions in Java

yes

proprietary syntax

Triggers

yes

User configurable commands triggered on index changes

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

online/offline synchronization between client and server

yes

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

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 in HA-Cluster

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

optimistic locking

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

News

On-device Vector Database for Dart/Flutter
21 May 2024

The first On-Device Vector Database: ObjectBox 4.0
16 May 2024

Edge AI: The era of on-device AI
23 April 2024

In-Memory Database Use Cases
15 February 2024

Data Viewer for Objects – announcing ObjectBox Admin
14 November 2023

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

Related products and services

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More resources

DB-Engines blog posts

Elasticsearch replaced Solr as the most popular search engine
12 January 2016, Paul Andlinger

Enterprise Search Engines almost double their popularity in the last 12 months
2 July 2014, Paul Andlinger

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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