DBMS > HarperDB vs. JanusGraph vs. KairosDB vs. RocksDB vs. SAP SQL Anywhere

System Properties Comparison HarperDB vs. JanusGraph vs. KairosDB vs. RocksDB vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

Distributed Time Series DBMS based on Cassandra or H2

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

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

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	2.02
Rank	#125	Overall
	#12	Graph DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

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

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

www.harperdb.io

janusgraph.org

github.com/kairosdb/kairosdb

rocksdb.org

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

Technical documentation

docs.harperdb.io/docs

docs.janusgraph.org

kairosdb.github.io

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

Developer

HarperDB

Linux Foundation; originally developed as Titan by Aurelius

Facebook, Inc.

SAP

formerly Sybase

Initial release

2017

2013

1992

Current release

3.1, August 2021

0.6.3, February 2023

1.2.2, November 2018

9.2.1, May 2024

17, July 2015

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

BSD

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

Node.js

Java

C++

Server operating systems

Linux
OS X

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

dynamic schema

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON data types

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

SQL

Support of SQL

SQL-like data manipulation statements

yes

APIs and other access methods

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Graphite protocol
HTTP REST
Telnet API

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Clojure
Java
Python

Java
JavaScript

Node.js
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

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

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

yes

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

A table resides as a whole on one (or more) nodes in a cluster

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

based on Cassandra

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

yes

selectable replication factor

based on Cassandra

yes

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using LMDB

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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

Access rights for users and roles

User authentification and security via Rexster Graph Server

simple password-based access control

fine grained access rights according to SQL-standard

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