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DBMS > CrateDB vs. InfinityDB vs. LeanXcale vs. Titan

System Properties Comparison CrateDB vs. InfinityDB vs. LeanXcale vs. Titan

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonInfinityDB  Xexclude from comparisonLeanXcale  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.
DescriptionDistributed Database based on LuceneA Java embedded Key-Value Store which extends the Java Map interfaceA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesTitan is a Graph DBMS optimized for distributed clusters.
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeKey-value store
Relational DBMS
Graph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#229  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.07
Rank#359  Overall
#54  Key-value stores
Score0.35
Rank#283  Overall
#41  Key-value stores
#128  Relational DBMS
Websitecratedb.comboilerbay.comwww.leanxcale.comgithub.com/­thinkaurelius/­titan
Technical documentationcratedb.com/­docsboilerbay.com/­infinitydb/­manualgithub.com/­thinkaurelius/­titan/­wiki
DeveloperCrateBoiler Bay Inc.LeanXcaleAurelius, owned by DataStax
Initial release2013200220152012
Current release4.0
License infoCommercial or Open SourceOpen SourcecommercialcommercialOpen Source infoApache license, version 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaJava
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMLinux
OS X
Unix
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or dateyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyes
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 indexesyesno infomanual creation possible, using inversions based on multi-value capabilityyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoyes infothrough Apache Derbyno
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
JavaC
Java
Scala
Clojure
Java
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes infovia pluggable storage backends
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelnoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infovia Faunus, a graph analytics engine
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynono infomanual creation possible, using inversions based on multi-value capabilityyesyes infoRelationships in graph
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategyACID infoOptimistic locking for transactions; no isolation for bulk loadsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.nonoyes
User concepts infoAccess controlrights management via user accountsnoUser authentification and security via Rexster Graph Server
More information provided by the system vendor
CrateDBInfinityDBLeanXcaleTitan
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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CrateDBInfinityDBLeanXcaleTitan
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