DBMS > Bangdb vs. HyperSQL vs. Solr vs. SpaceTime

System Properties Comparison Bangdb vs. HyperSQL vs. Solr vs. SpaceTime

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Search engine

Spatial DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

bangdb.com

hsqldb.org

solr.apache.org

www.mireo.com/spacetime

Technical documentation

docs.bangdb.com

hsqldb.org/web/hsqlDocsFrame.html

solr.apache.org/resources.html

Developer

Sachin Sinha, BangDB

Apache Software Foundation

Mireo

Initial release

2012

2001

2006

2020

Current release

BangDB 2.0, October 2021

2.7.2, June 2023

9.6.0, April 2024

License

Commercial or Open Source

Open Source

BSD 3

Open Source

based on BSD license

Open Source

Apache Version 2

commercial

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, C++

Java

C++

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

All OS with a Java VM

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

Linux

Data scheme

schema-free

yes

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

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL like support with command line tool

yes

Solr Parallel SQL Interface

A subset of ANSI SQL is implemented

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

Java API
RESTful HTTP/JSON API

RESTful HTTP API

Supported programming languages

C
C#
C++
Java
Python

All languages supporting JDBC/ODBC
Java

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

C#
C++
Python

Server-side scripts

Stored procedures

Java, SQL

Java plugins

Triggers

yes, Notifications (with Streaming only)

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

none

Sharding

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

none

yes

Real-time block device replication (DRBD)

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

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

fine grained access rights according to SQL-standard

yes

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More resources

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