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DBMS > Apache IoTDB vs. HugeGraph vs. Ignite vs. ScyllaDB

System Properties Comparison Apache IoTDB vs. HugeGraph vs. Ignite vs. ScyllaDB

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonHugeGraph  Xexclude from comparisonIgnite  Xexclude from comparisonScyllaDB  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkA fast-speed and highly-scalable Graph DBMSApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Cassandra and DynamoDB compatible wide column store
Primary database modelTime Series DBMSGraph DBMSKey-value store
Relational DBMS
Wide column store
Secondary database modelsKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score4.75
Rank#68  Overall
#5  Wide column stores
Websiteiotdb.apache.orggithub.com/­hugegraph
hugegraph.apache.org
ignite.apache.orgwww.scylladb.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlhugegraph.apache.org/­docsapacheignite.readme.io/­docsdocs.scylladb.com
DeveloperApache Software FoundationBaiduApache Software FoundationScyllaDB
Initial release2018201820152015
Current release1.1.0, April 20230.9Apache Ignite 2.6ScyllaDB Open Source 5.4.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0Open Source infoOpen Source (AGPL), commercial license available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC++, Java, .NetC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Unix
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonoyesno
Secondary indexesyesyes infoalso supports composite index and range indexyesyes infocluster global secondary indices
SQL infoSupport of SQLSQL-like query languagenoANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statements (CQL)
APIs and other access methodsJDBC
Native API
Java API
RESTful HTTP API
TinkerPop Gremlin
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Proprietary protocol (CQL) infocompatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Groovy
Java
Python
C#
C++
Java
PHP
Python
Ruby
Scala
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
Server-side scripts infoStored proceduresyesasynchronous Gremlin script jobsyes (compute grid and cache interceptors can be used instead)yes, Lua
Triggersyesnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yes infodepending on used storage backend, e.g. Cassandra and HBaseShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyes infodepending on used storage backend, e.g. Cassandra and HBaseyes (replicated cache)selectable replication factor infoRepresentation of geographical distribution of servers is possible
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkvia hugegraph-sparkyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Eventual ConsistencyImmediate ConsistencyEventual Consistency
Tunable Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno infoAtomicity and isolation are supported for single operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes infoin-memory tables
User concepts infoAccess controlyesUsers, roles and permissionsSecurity Hooks for custom implementationsAccess rights for users can be defined per object
More information provided by the system vendor
Apache IoTDBHugeGraphIgniteScyllaDB
Specific characteristicsScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more
Competitive advantagesHighly-performant (efficiently utilizes full resources of a node and network; millions...
» more
Typical application scenariosScyllaDB is ideal for applications that require high throughput and low latency at...
» more
Key customersDiscord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
» more
Market metricsScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
» more
Licensing and pricing modelsScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
» more

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Apache IoTDBHugeGraphIgniteScyllaDB
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