DBMS > AnzoGraph DB vs. FoundationDB vs. Ingres vs. Kdb vs. RocksDB

System Properties Comparison AnzoGraph DB vs. FoundationDB vs. Ingres vs. Kdb vs. RocksDB

Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Ordered key-value store. Core features are complimented by layers.

Well established RDBMS

High performance Time Series DBMS

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

Primary database model

Graph DBMS
RDF store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Time Series DBMS
Vector DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

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

Website

cambridgesemantics.com/anzograph

github.com/apple/foundationdb

www.actian.com/databases/ingres

kx.com

rocksdb.org

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

apple.github.io/foundationdb

docs.actian.com/ingres

code.kx.com

github.com/facebook/rocksdb/wiki

Developer

Cambridge Semantics

FoundationDB

Actian Corporation

Kx Systems, a division of First Derivatives plc

Facebook, Inc.

Initial release

2018

2013

1974

originally developed at University Berkely in early 1970s

2000

kdb was released 2000, kdb+ in 2003

2013

Current release

2.3, January 2021

6.2.28, November 2020

11.2, May 2022

3.6, May 2018

8.11.4, April 2024

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

commercial

free 32-bit version

Open Source

BSD

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++

Server operating systems

Linux

Linux
OS X
Windows

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

some layers support schemas

yes

schema-free

Typing

predefined data types such as float or date

some layers support typing

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

table attribute 'grouped'

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

supported in specific SQL layer only

yes

SQL-like query language (q)

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

C++ API
Java API

Supported programming languages

C++
Java
Python

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

in SQL-layer only

yes

user defined functions

Triggers

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Ingres Replicator

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

in SQL-layer only

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

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

Access rights for users and roles

fine grained access rights according to SQL-standard

rights management via user accounts

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
» more

Licensing and pricing models

upon request
» more

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.