DBMS > InfinityDB vs. OpenTSDB vs. ScyllaDB vs. Stardog

System Properties Comparison InfinityDB vs. OpenTSDB vs. ScyllaDB vs. Stardog

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Editorial information provided by DB-Engines

Name

Description

A Java embedded Key-Value Store which extends the Java Map interface

Scalable Time Series DBMS based on HBase

Cassandra and DynamoDB compatible wide column store

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Secondary database models

Key-value store

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

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	4.75
Rank	#68	Overall
	#5	Wide column stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

Technical documentation

boilerbay.com/infinitydb/manual

opentsdb.net/docs/build/html/index.html

docs.scylladb.com

docs.stardog.com

Developer

Boiler Bay Inc.

currently maintained by Yahoo and other contributors

ScyllaDB

Stardog-Union

Initial release

2002

2011

2015

2010

Current release

4.0

ScyllaDB Open Source 5.4.1, January 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

LGPL

Open Source

Open Source (AGPL), commercial license available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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.

Scylla Cloud: Create real-time applications that run at global scale with Scylla Cloud, the industry’s most powerful NoSQL DBaaS

Implementation language

Java

C++

Java

Server operating systems

All OS with a Java VM

Linux
Windows

Linux

Linux
macOS
Windows

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

numeric data for metrics, strings for tags

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.

Import/export of XML data possible

Secondary indexes

manual creation possible, using inversions based on multi-value capability

yes

cluster global secondary indices

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like DML and DDL statements (CQL)

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

HTTP API
Telnet API

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

Java

Erlang
Go
Java
Python
R
Ruby

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes, Lua

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

based on HBase

selectable replication factor

Representation of geographical distribution of servers is possible

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Immediate Consistency

based on HBase

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

yes

relationships in graphs

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

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

in-memory tables

yes

User concepts

Access control

Access rights for users can be defined per object

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more

Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
» more

Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
» more

Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more

Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more

Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources

DB-Engines blog posts

Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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