DBMS > Firebolt vs. H2 vs. SAP HANA vs. Solr vs. SQLite

System Properties Comparison Firebolt vs. H2 vs. SAP HANA vs. Solr vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

In-memory, column based data store. Available as appliance or cloud service

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

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Spatial DBMS

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

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.firebolt.io

www.h2database.com

www.sap.com/products/hana.html

solr.apache.org

www.sqlite.org

Technical documentation

docs.firebolt.io

www.h2database.com/html/main.html

help.sap.com/hana

solr.apache.org/resources.html

www.sqlite.org/docs.html

Developer

Firebolt Analytics Inc.

Thomas Mueller

SAP

Apache Software Foundation

Dwayne Richard Hipp

Initial release

2020

2005

2010

2006

2000

Current release

2.2.220, July 2023

2.0 SPS07 (April 4, 2023), April 2023

9.6.1, May 2024

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

Apache Version 2

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

hosted

All OS with a Java VM

Appliance or cloud-service

All OS with a Java VM

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

server-less

Data scheme

yes

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

yes

dynamic column types

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL-92 is not fully supported

APIs and other access methods

.Net
ODBC
RESTful HTTP API

JDBC
ODBC

Java API
RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Go
JavaScript (Node.js)
Python

Java

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

SQLScript, R

Java plugins

Triggers

yes

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

none

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

yes

Transaction concepts

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

ACID

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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

fine grained access rights according to SQL-standard

yes

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