DBMS > Apache Phoenix vs. Datomic vs. Dragonfly vs. RocksDB vs. SAP Advantage Database Server

System Properties Comparison Apache Phoenix vs. Datomic vs. Dragonfly vs. RocksDB vs. SAP Advantage Database Server

Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

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

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	1.97
Rank	#126	Overall
	#59	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	0.41
Rank	#266	Overall
	#38	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

phoenix.apache.org

www.datomic.com

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

rocksdb.org

www.sap.com/products/advantage-database-server.html

Technical documentation

phoenix.apache.org

docs.datomic.com

www.dragonflydb.io/docs

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Cognitect

DragonflyDB team and community contributors

Facebook, Inc.

Sybase, SAP

Initial release

2014

2012

2023

2013

1993

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

1.0.6735, June 2023

1.0, March 2023

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

Open Source

BSL 1.1

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

Java

Java, Clojure

C++

Server operating systems

Linux
Unix
Windows

All OS with a Java VM

Linux

Linux
Windows

Data scheme

yes

late-bound, schema-on-read capabilities

yes

scheme-free

schema-free

yes

Typing

predefined data types such as float or date

yes

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

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC

RESTful HTTP API

Proprietary protocol

RESP - REdis Serialization Protocol

C++ API
Java API

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

Clojure
Java

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

C
C++
Go
Java
Perl
Python
Ruby

Delphi
Perl
PHP

Server-side scripts

Stored procedures

user defined functions

yes

Transaction Functions

Lua

yes

Triggers

By using transaction functions

publish/subscribe channels provide some trigger functionality

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

But extensive use of caching in the application peers

Source-replica replication

yes

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or 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

Atomic execution of command blocks and scripts

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, strict serializability by the server

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

yes

caching of (temporary) tables can be configured

User concepts

Access control

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

Password-based authentication

fine grained access rights according to SQL-standard

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