DBMS > Bangdb vs. Heroic vs. NSDb vs. RocksDB vs. SAP SQL Anywhere

System Properties Comparison Bangdb vs. Heroic vs. NSDb vs. RocksDB vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

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

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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)

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

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

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

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

bangdb.com

github.com/spotify/heroic

nsdb.io

rocksdb.org

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

Technical documentation

docs.bangdb.com

spotify.github.io/heroic

nsdb.io/Architecture

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Sachin Sinha, BangDB

Spotify

Facebook, Inc.

SAP

formerly Sybase

Initial release

2012

2014

2017

2013

1992

Current release

BangDB 2.0, October 2021

9.2.1, May 2024

17, July 2015

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

Apache Version 2.0

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Java

Java, Scala

C++

Server operating systems

Linux

Linux
macOS

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

yes: int, bigint, decimal, string

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

via Elasticsearch

all fields are automatically indexed

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

HQL (Heroic Query Language, a JSON-based language)
HTTP API

gRPC
HTTP REST
WebSocket

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

Java
Scala

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

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

Triggers

yes, Notifications (with Streaming only)

yes

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

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Eventual Consistency
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

yes

ACID

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

Using Apache Lucene

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

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