DBMS > Dgraph vs. Dragonfly vs. H2 vs. SAP Adaptive Server vs. SQLite

System Properties Comparison Dgraph vs. Dragonfly vs. H2 vs. SAP Adaptive Server vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

A drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instance

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

The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMS

Widely used embeddable, in-process RDBMS

Primary database model

Graph DBMS

Key-value store

Relational DBMS

Secondary database models

Spatial DBMS

with Boeing's Spatial Query Server

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

Score	1.53
Rank	#152	Overall
	#15	Graph DBMS

Score	0.49
Rank	#261	Overall
	#38	Key-value stores

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	35.09
Rank	#25	Overall
	#17	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

dgraph.io

github.com/dragonflydb/dragonfly
www.dragonflydb.io

www.h2database.com

www.sap.com/products/technology-platform/sybase-ase.html

www.sqlite.org

Technical documentation

dgraph.io/docs

www.dragonflydb.io/docs

www.h2database.com/html/main.html

help.sap.com/docs/SAP_ASE

www.sqlite.org/docs.html

Developer

Dgraph Labs, Inc.

DragonflyDB team and community contributors

Thomas Mueller

SAP, Sybase

Dwayne Richard Hipp

Initial release

2016

2023

2005

1987

2000

Current release

1.0, March 2023

2.2.220, July 2023

16.0

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSL 1.1

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

Public Domain

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

C++

Java

C and C++

Server operating systems

Linux
OS X
Windows

Linux

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Unix
Windows

server-less

Data scheme

schema-free

scheme-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

strings, hashes, lists, sets, sorted sets, bit arrays

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL

Support of SQL

yes

SQL-92 is not fully supported

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl

Java

C
C++
Cobol
Java
Java
Perl
PHP
Python

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Lua

Java Stored Procedures and User-Defined Functions

Java and Transact-SQL

Triggers

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

yes

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

Source-replica replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

Atomic execution of command blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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

Planned for future releases

Password-based authentication

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.