DBMS > Derby vs. HarperDB vs. Machbase Neo vs. TigerGraph

System Properties Comparison Derby vs. HarperDB vs. Machbase Neo vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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.

TimeSeries DBMS for AIoT and BigData

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

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

Score	4.60
Rank	#70	Overall
	#38	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

Technical documentation

db.apache.org/derby/manuals/index.html

docs.harperdb.io/docs

machbase.com/dbms

docs.tigergraph.com

Developer

Apache Software Foundation

HarperDB

Machbase

Initial release

1997

2017

2013

2017

Current release

10.17.1.0, November 2023

3.1, August 2021

V8.0, August 2023

License

Commercial or Open Source

Open Source

Apache version 2

commercial

free community edition available

commercial

free test version available

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

Java

Node.js

C++

Server operating systems

All OS with a Java VM

Linux
OS X

Linux
macOS
Windows

Linux

Data scheme

yes

dynamic schema

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

yes

SQL-like data manipulation statements

SQL-like query language

SQL-like query language (GSQL)

APIs and other access methods

JDBC

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

Java

.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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C++
Java

Server-side scripts

Stored procedures

Java Stored Procedures

Custom Functions

since release 3.1

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

the nodes on which a table resides can be defined

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

volatile and lookup table

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles

simple password-based access control

Role-based access control

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More resources

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