DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Galaxybase vs. Hawkular Metrics vs. Titan

System Properties Comparison Galaxybase vs. Hawkular Metrics vs. Titan

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGalaxybase  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonTitan  Xexclude from comparison
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.
DescriptionScalable, ACID-compliant native distributed parallel graph platformHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Titan is a Graph DBMS optimized for distributed clusters.
Primary database modelGraph DBMSTime Series DBMSGraph DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.04
Rank#375  Overall
#40  Graph DBMS
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Websitegalaxybase.comwww.hawkular.orggithub.com/­thinkaurelius/­titan
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidegithub.com/­thinkaurelius/­titan/­wiki
DeveloperChuanglin(Createlink) Technology Co., Ltd 浙江创邻科技有限公司Community supported by Red HatAurelius, owned by DataStax
Initial release201720142012
Current releaseNov 20, November 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and JavaJavaJava
Server operating systemsLinuxLinux
OS X
Windows
Linux
OS X
Unix
Windows
Data schemeStrong typed schemaschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLnonono
APIs and other access methodsBrowser interface
console (shell)
Graph API (Gremlin)
OpenCypher
Proprietary native API
HTTP RESTJava API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languagesGo
Java
Python
Go
Java
Python
Ruby
Clojure
Java
Python
Server-side scripts infoStored proceduresuser defined procedures and functionsnoyes
Triggersyes infovia Hawkular Alertingyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandrayes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor infobased on Cassandrayes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyes infoRelationships in graphsnoyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlRole-based access controlnoUser authentification and security via Rexster Graph Server

More information provided by the system vendor

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
GalaxybaseHawkular MetricsTitan
DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

show all

Recent citations in the news

做国产图数据库,「创邻科技」将拓展国际市场| 新科技创业
5 April 2023, 36kr

创邻科技,位居IDC MarketScape中国图数据库市场领导者类别
13 September 2023, CSDN

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services
24 August 2015, AWS Blog

Beyond Titan: The Evolution of DataStax's New Graph Database
21 June 2016, Datanami

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

DataStax acquires Aurelius, the startup behind the Titan graph database
3 February 2015, VentureBeat

DSE Graph review: Graph database does double duty
14 November 2019, InfoWorld

provided by Google News



Share this page

Featured Products

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it free.

Present your product here