DBMS > Hawkular Metrics vs. Interbase vs. KeyDB vs. Microsoft Access vs. RocksDB

System Properties Comparison Hawkular Metrics vs. Interbase vs. KeyDB vs. Microsoft Access vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Light-weight proven RDBMS

originally from Borland

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

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

Primary database model

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

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

Website

www.hawkular.org

www.embarcadero.com/products/interbase

github.com/Snapchat/KeyDB
keydb.dev

www.microsoft.com/en-us/microsoft-365/access

rocksdb.org

Technical documentation

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.embarcadero.com/products/interbase

docs.keydb.dev

developer.microsoft.com/en-us/access

github.com/facebook/rocksdb/wiki

Developer

Community supported by Red Hat

Embarcadero

EQ Alpha Technology Ltd.

Microsoft

Facebook, Inc.

Initial release

2014

1984

2019

1992

2013

Current release

InterBase 2020, December 2019

1902 (16.0.11328.20222), March 2019

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD-3

commercial

Bundled with Microsoft Office

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

Java

C++

Server operating systems

Linux
OS X
Windows

Android
iOS
Linux
OS X
Windows

Linux

Windows

Not a real database server, but making use of DLLs

Linux

Data scheme

schema-free

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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.

export as XML data possible

Secondary indexes

yes

by using the Redis Search module

yes

SQL

Support of SQL

yes

but not compliant to any SQL standard

APIs and other access methods

HTTP REST

ADO.NET
JDBC
ODBC

Proprietary protocol

RESP - REdis Serialization Protoco

ADO.NET
DAO
ODBC
OLE DB

C++ API
Java API

Supported programming languages

Go
Java
Python
Ruby

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Interbase procedure and trigger language

Lua

yes

since Access 2010 using the ACE-engine

Triggers

yes

via Hawkular Alerting

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Interbase Change Views

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

ACID

but no files for transaction logging

yes

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

but no files for transaction logging

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

fine grained access rights according to SQL-standard

simple password-based access control and ACL

a simple user-level security was built in till version Access 2003

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