DBMS > Apache Drill vs. BoltDB vs. IRONdb vs. RocksDB vs. Solr

System Properties Comparison Apache Drill vs. BoltDB vs. IRONdb vs. RocksDB vs. Solr

Editorial information provided by DB-Engines

Name

IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

An embedded key-value store for Go.

A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicity

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Document store
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

drill.apache.org

github.com/boltdb/bolt

www.circonus.com/solutions/time-series-database/

rocksdb.org

solr.apache.org

Technical documentation

drill.apache.org/docs

docs.circonus.com/irondb/category/getting-started

github.com/facebook/rocksdb/wiki

solr.apache.org/resources.html

Developer

Apache Software Foundation

Circonus LLC.

Facebook, Inc.

Apache Software Foundation

Initial release

2012

2013

2017

2013

2006

Current release

1.20.3, January 2023

V0.10.20, January 2018

9.2.1, May 2024

9.6.1, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

commercial

Open Source

BSD

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

C and C++

C++

Java

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Solaris
Windows

Linux

All OS with a Java VM

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

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

text, numeric, histograms

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

SQL SELECT statement is SQL:2003 compliant

SQL-like query language (Circonus Analytics Query Language: CAQL)

Solr Parallel SQL Interface

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

HTTP API

C++ API
Java API

Java API
RESTful HTTP/JSON API

Supported programming languages

C++

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

user defined functions

yes, in Lua

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Automatic, metric affinity per node

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

configurable replication factor, datacenter aware

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate consistency per node, eventual consistency across nodes

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

yes

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