DBMS > atoti vs. Solr vs. Transbase vs. Warp 10

System Properties Comparison atoti vs. Solr vs. Transbase vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

A resource-optimized, high-performance, universally applicable RDBMS

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

atoti.io

solr.apache.org

www.transaction.de/en/products/transbase.html

www.warp10.io

Technical documentation

docs.atoti.io

solr.apache.org/resources.html

www.transaction.de/en/products/transbase/features.html

www.warp10.io/content/02_Getting_started

Developer

ActiveViam

Apache Software Foundation

Transaction Software GmbH

SenX

Initial release

2006

1987

2015

Current release

9.6.0, April 2024

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

free versions available

Open Source

Apache Version 2

commercial

free development license

Open Source

Apache License 2.0

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

All OS with a Java VM

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

FreeBSD
Linux
macOS
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

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

yes

schema-free

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

Multidimensional Expressions (MDX)

Solr Parallel SQL Interface

yes

APIs and other access methods

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

HTTP API
Jupyter
WebSocket

Supported programming languages

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

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

Python

Java plugins

yes

WarpScript

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

based on HBase

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

Eventual Consistency

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

optimistic locking

yes

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

yes

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

More information provided by the system vendor

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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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