DBMS > NSDb vs. RocksDB vs. RRDtool vs. SAP SQL Anywhere vs. Splice Machine

System Properties Comparison NSDb vs. RocksDB vs. RRDtool vs. SAP SQL Anywhere vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

Industry standard data logging and graphing tool for time series data. RRD is an acronym for round-robin database.

The data is stored in a circular buffer, thus the system storage footprint remains constant over time.

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

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

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

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

Score	1.90
Rank	#132	Overall
	#11	Time Series DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

nsdb.io

rocksdb.org

oss.oetiker.ch/rrdtool

www.sap.com/products/technology-platform/sql-anywhere.html

splicemachine.com

Technical documentation

nsdb.io/Architecture

github.com/facebook/rocksdb/wiki

oss.oetiker.ch/rrdtool/doc

help.sap.com/docs/SAP_SQL_Anywhere

splicemachine.com/how-it-works

Developer

Facebook, Inc.

Tobias Oetiker

SAP

formerly Sybase

Splice Machine

Initial release

2017

2013

1999

1992

2014

Current release

9.2.1, May 2024

1.8.0, 2022

17, July 2015

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

BSD

Open Source

GPL V2 and FLOSS

commercial

Open Source

AGPL 3.0, commercial license available

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

Java, Scala

C++

Implementations in Java (e.g. RRD4J) and C# available

Java

Server operating systems

Linux
macOS

Linux

HP-UX
Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: int, bigint, decimal, string

Numeric data only

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.

Exporting into and restoring from XML files possible

yes

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

gRPC
HTTP REST
WebSocket

C++ API
Java API

in-process shared library
Pipes

ADO.NET
HTTP API
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java
Scala

C
C++
Go
Java
Perl
Python
Ruby

with librrd library
C#

with a different implementation of RRDTool
Java

with a different implementation of RRDTool
JavaScript (Node.js)

with a different implementation of RRDTool
Lua
Perl
PHP

with a wrapper library
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes, in C/C++, Java, .Net or Perl

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

Database mirroring

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

by using the rrdcached daemon

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

Using Apache Lucene

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

Access rights for users, groups and roles according to SQL-standard

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