DBMS > RocksDB vs. SpaceTime vs. Spark SQL

System Properties Comparison RocksDB 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)

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

Key-value store

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

rocksdb.org

www.mireo.com/spacetime

spark.apache.org/sql

Technical documentation

github.com/facebook/rocksdb/wiki

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

Developer

Facebook, Inc.

Mireo

Apache Software Foundation

Initial release

2013

2020

2014

Current release

8.11.4, April 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

BSD

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

C++

Scala

Server operating systems

Linux

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

Secondary indexes

SQL

Support of SQL

A subset of ANSI SQL is implemented

SQL-like DML and DDL statements

APIs and other access methods

C++ API
Java API

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
C++
Go
Java
Perl
Python
Ruby

C#
C++
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

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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