DBMS > Apache Druid vs. BigchainDB vs. Splice Machine vs. SQL.JS vs. Titan

System Properties Comparison Apache Druid vs. BigchainDB vs. Splice Machine vs. SQL.JS 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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Port of SQLite to JavaScript

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

Graph DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Website

github.com/thinkaurelius/titan

Technical documentation

druid.apache.org/docs/latest/design

bigchaindb.readthedocs.io/en/latest

splicemachine.com/how-it-works

sql.js.org/documentation/index.html

github.com/thinkaurelius/titan/wiki

Developer

Apache Software Foundation and contributors

Splice Machine

Alon Zakai

enhancements implemented by others

Aurelius, owned by DataStax

Initial release

2012

2016

2014

2012

Current release

29.0.1, April 2024

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

AGPL v3

Open Source

AGPL 3.0, commercial license available

Open Source

Apache license, version 2.0

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

Python

Java

JavaScript

Java

Server operating systems

Linux
OS X
Unix

Linux

Linux
OS X
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

Linux
OS X
Unix
Windows

Data scheme

yes

schema-less columns are supported

schema-free

yes

Typing

predefined data types such as float or date

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

SQL for querying

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
RESTful HTTP/JSON API

CLI Client
RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

JavaScript API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

JavaScript

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

selectable replication factor

Multi-source replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

except by serializing a db to a file

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

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

yes

Access rights for users, groups and roles according to SQL-standard

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

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