DBMS > FileMaker vs. Google BigQuery vs. Memcached vs. Quasardb vs. Titan

System Properties Comparison FileMaker vs. Google BigQuery vs. Memcached vs. Quasardb vs. Titan

Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Large scale data warehouse service with append-only tables

In-memory key-value store, originally intended for caching

Distributed, high-performance timeseries database

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

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

Score	48.20
Rank	#20	Overall
	#14	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Website

www.claris.com/filemaker

cloud.google.com/bigquery

www.memcached.org

quasar.ai

github.com/thinkaurelius/titan

Technical documentation

www.claris.com/resources/documentation

cloud.google.com/bigquery/docs

github.com/memcached/memcached/wiki

doc.quasar.ai/master

github.com/thinkaurelius/titan/wiki

Developer

Claris

a subsidiary of Apple

Google

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

quasardb

Aurelius, owned by DataStax

Initial release

1983

2010

2003

2009

2012

Current release

19.4.1, November 2021

1.6.25, March 2024

3.14.1, January 2024

License

Commercial or Open Source

commercial

Open Source

BSD license

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

Server operating systems

iOS

client part only
Linux
OS X
Windows

hosted

FreeBSD
Linux
OS X
Unix
Windows

BSD
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

integer and binary

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

A http query request can return the data in XML format

Secondary indexes

yes

with tags

yes

SQL

Support of SQL

yes

via plugins

yes

SQL-like query language

APIs and other access methods

Filemaker WebDirect
JDBC
ODBC

RESTful HTTP/JSON API

Proprietary protocol

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

PHP

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

consistent hashing

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication, warm standby

since Version 14

none

Repcached, a Memcached patch, provides this functionallity

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

simple rights management via user accounts and connection to external directory services

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

yes

using SASL (Simple Authentication and Security Layer) protocol

Cryptographically strong user authentication and audit trail

User authentification and security via Rexster Graph Server

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