DBMS > RocksDB vs. Solr vs. SpaceTime vs. Spark SQL

System Properties Comparison RocksDB vs. Solr vs. SpaceTime vs. Spark SQL

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Editorial information provided by DB-Engines

Name

Description

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

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

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

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Secondary database models

Spatial DBMS

Relational DBMS

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

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

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

rocksdb.org

solr.apache.org

www.mireo.com/spacetime

spark.apache.org/sql

Technical documentation

github.com/facebook/rocksdb/wiki

solr.apache.org/resources.html

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Facebook, Inc.

Apache Software Foundation

Mireo

Apache Software Foundation

Initial release

2013

2006

2020

2014

Current release

9.2.1, May 2024

9.6.1, May 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

BSD

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Java

C++

Scala

Server operating systems

Linux

All OS with a Java VM

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

Linux

Linux
OS X
Windows

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

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

SQL

Support of SQL

Solr Parallel SQL Interface

A subset of ANSI SQL is implemented

SQL-like DML and DDL statements

APIs and other access methods

C++ API
Java API

Java API
RESTful HTTP/JSON API

RESTful HTTP API

JDBC
ODBC

Supported programming languages

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

C#
C++
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Fixed-grid hypercubes

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Real-time block device replication (DRBD)

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

Eventual Consistency

Immediate 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

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

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